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The central feature of this novel reflex-tree architecture is inspired by a fundamental element of the human nervous system -- reflex arcs, or neuro-muscular reactions and instinctive motions in response to urgent situations that do not require the direct intervention of the brain. The scientific foundation and engineering framework built by this project will pave the way for enhanced monitoring and management of critical smart city infrastructure, from gas/oil pipelines, water management, communication networks, and power grids, to public transportation and healthcare. The interdisciplinary and collaborative nature of the project will inspire broader participation in related areas of research.<br /><br />Within the human body, a neural reflex arc is able to cause an individual to immediately react to a source of discomfort without the need for direct control from the brain. The reflex-tree architecture mimics such human neural circuits, using massive numbers of intermediate computing nodes, edge devices, and sensors to gather, process, and, most importantly, to react to data concerning critical infrastructure elements. Key innovations of the proposed reflex-tree architecture include: 1) A novel, 4-level, large scale, and application-specific hierarchical computing and communication structure capable of carrying out sensor-based decision-making processes. The required computation and nodal computing power increases at each successive stage in the hierarchy, with the level-1 cloud performing the most complex tasks. 2) A densely distributed fiber-optic sensing network and parallel machine learning algorithms will be developed targeting smart city applications. 3) Novel, complementary machine intelligence algorithms will be developed, providing accurate control decisions via multi-layer adaptive learning, spatial-temporal association, and complex system behavior analysis. 4) New parallel algorithms and software run-time environments will be proposed and developed that are specifically tailored to the novel reflex-tree system architecture.<br /><br />To demonstrate the feasibility and performance of the reflex-tree architecture, a proof-of-concept prototype will be constructed utilizing a miniaturized, laboratory-scale municipal gas pipeline system. The prototype will incorporate a complete 4-level reflex-tree--a distributed fiber-optic sensing network deployed alongside pipelines, edge devices performing data classification using parallel SVM, intermediate nodes performing massively-parallel spatial and temporal machine learning, and the cloud as the root node running sophisticated parallel behavioral analysis and decision making tasks. The resulting system is a cross layer, high performance, and massively parallel computing platform, providing a foundational sensing and computer architecture for future smart cities.","FID":1}},{"geometry":{"x":-1.3050974968346935E7,"y":3883033.1581039284,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"CIF21 DIBBs: Ubiquitous Access to Transient Data and Preliminary Results via the SeedMe Platform","Organization":"University of California-San Diego","City":"La Jolla","State":"CA","Abstract":"Computational simulations have become an indispensible tool in a wide variety of science and engineering investigations. Quick and effective assessments of the resulting data are necessary for efficient use of researcher time and computation resources, but this process is complicated when a large collaborating team is geographically dispersed and/or some team members do not have direct access to the computation resource and output data. Current methods for sharing and assessing transient data and preliminary results are cumbersome and labor intensive; each research team must create their own scripts and ad hoc procedures to push data from system to system and user to user. Better tools and cyberinfrastructure are needed to support preliminary results sharing for collaborating computational science teams. <br /><br />This project develops web-based building blocks and cyberinfrastructure to enable easy sharing and streaming of transient data and preliminary results from computing resources to a variety of platforms, from mobile devices to workstations, making it possible to quickly and conveniently view and assess results and provide an essential missing component in High Performance Computing and cloud computing infrastructure.","FID":2}},{"geometry":{"x":-1.3609527145463023E7,"y":4561442.890345454,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"CI-ADDO-NEW: CRCNS.ORG - online repository for high-quality neuroscience data and resources for computational neuroscience","Organization":"University of California-Berkeley","City":"Berkeley","State":"CA","Abstract":"This project will develop and operate a community infrastructure, CRCNS.ORG, to enable the sharing of data needed by the computational neuroscience community, to enhance and foster collaborations among theoretical and experimental researchers, and to further the development and testing of computational theories of brain function. This infrastructure will widen the spectrum of techniques applied to brain data, enabling discoveries that go beyond the scopes of individual laboratories.<br /><br />The infrastructure targets the communities of neuroscience and related fields such as computer science, physics, mathematics, statistics, and engineering in which investigators seek access to high-quality neurophysiology data, including electrical, magnetic, and optical recordings from single neurons, neural ensembles, and brain regions. Development activities are aimed at lowering the barriers to contributing, accessing, and using neurophysiology data. Standardized methods will be developed for storing and annotating data in a self-describing, hierarchical format, and enabling flexible on-line access. Scalable methods will be developed to enable users to find potentially useful data and to provide means for online visualization and some on-line analysis. Operations activities will support users and data contributors as well as community outreach activities. Three summer training courses will be held to introduce students and researchers to methods and conventions concerning organization, visualization, and analysis of neuroscience data, and how to use the specific resources of the repository.","FID":3}},{"geometry":{"x":-1.3702153228044456E7,"y":5473171.20596563,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Geospatial Thinking Framework","Organization":"University of Oregon Eugene","City":"Eugene","State":"OR","Abstract":"Geospatial thinking has become an important focus in understanding human spatial behaviors, but meaningful definitions, theories, and models of geospatial thinking are lacking. This interdisciplinary research project will address these gaps in knowledge by examining the behavioral and neurological correlates of geospatial thinking. Geospatial thinking is primarily a cognitive construct, occurring in the human brain. This project aims to develop a robust model that will have foundations in behavioral and cognitive neurogeography and will represent a new way to conceptualize and investigate geospatial thinking. This project will contribute new insights regarding neurogeography that are different from more traditional investigations of spatial cognition in neuroscience by placing emphasis on the ecological validity of geospatial tasks, issues, and questions. In doing so, it will focus on the grounding of geospatial activities in real-world activities and will consider the on-the-ground nature of the questions that are under investigation. The project will provide special research and training opportunities for graduate and undergraduate students.<br /><br />The investigators will generate research questions for this project from a synthesized Geospatial Thinking Framework, which includes three axes: space, time, and attribute. Geospatial thinking skills will be organized based on category (the axes) and complexity (position relative to origin). Two research questions will be posed. What is the relationship between each geospatial thinking skill and the geographic primitives as represented by the framework axes? What is the relative complexity of each geospatial thinking skill as represented by distance from axes origin? These research questions will be investigated through a combined methodology of behavioral testing and neuroimaging (functional Magnetic Resonance Imaging, fMRI). Behavioral testing will include traditional and newly-developed measures of performance on geospatial cognition tasks. All measurement instruments will be assessed for reliability and validity (if not already available). The fMRI methods will include both block and event-related designs. Analysis will focus on the blood-oxygen-level dependent signal detection for both the whole brain as well as the specific parts of the brain of most interest, which is especially relevant for dorsal and ventral analyses.","FID":4}},{"geometry":{"x":-9433519.478638258,"y":4795061.084422266,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Configural Face Processing and Prejudice Regulation","Organization":"Miami University","City":"Oxford","State":"OH","Abstract":"Dehumanization - the denial of full humanness to others - is a key trigger for mistreating other people. When others are dehumanized, they are often subjected to aggression, experience discrimination, and others even become blind to their pain. In the current research, Kurt Hugenberg (Miami University) and colleagues will examine the facial signals that can lead to dehumanization of others. Past research has shown that human faces are normally processed configurally. That is, rather than examining specific features (the eyes, the nose) of the face separately, the features of a face are spontaneously \"grouped together\" and processed as a whole. This work will investigate whether a failure to perform this configural processing for a face may trigger dehumanization. This proposed research will 1) bridge the boundary between perceptual and social psychology, 2) expand our limited understanding of the perceptual mechanisms underlying dehumanization, and 3) answer deep questions about both the antecedents and effects of dehumanization and the malleability of face processing. Dehumanization plays a key role in intergroup conflict, injustice, and discrimination. Understanding the mechanisms underlying judgments of humanness is a necessary next step to addressing the causes and consequences of dehumanization.<br /><br />The proposed studies will explore the relationships between ascribing humanity and configural face processing in 10 experiments across 3 lines of research. The first line of work may provide novel evidence that configural face processing is a cue for humanity, with configurally processed faces making human faces seem more human, and that disruptions of configural processing may trigger dehumanization. Second, using both behavioral and neuroscience (ERP) techniques, this work will investigate whether increasing ascriptions of humanity can increase the extent of configural face processing. Third, the current research will seek to extend the findings regarding configural face processing and dehumanization to the domain of prejudice regulation. Whereas the activation of prejudice can occur simply from race-typical facial features, the motivation to control prejudice could be triggered by experiencing a face as fully human. Thus, this third line of work will demonstrate that prejudice activation and prejudice regulation are dissociable, such that the former can be triggered by race-typical features alone, and the latter via configural processing. This knowledge could lead to the development of novel strategies to effectively reduce prejudice and discrimination.","FID":5}},{"geometry":{"x":-8309449.105938767,"y":4919816.456593225,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Toward a Theory of Real Neural Networks","Organization":"Princeton University","City":"Princeton","State":"NJ","Abstract":"Project: Our perception of the world seems a coherent whole, yet it is built out of the activities of many thousands or even millions of neurons, and similarly for our memories, thoughts, and actions. It seems difficult to understand the emergence of behavioral and phenomenal coherence unless the underlying neural activity also is coherent. But if the neurons are not independent, how do we describe their collective activity? In this work, The PI takes several approaches to this problem. In each case the PI is reaching for a theoretical framework with a generality that transcends the details of particular systems, but in each case the work is grounded by intimate collaboration with several experimental groups. It is now conventional to assert that the emergence of new, larger data sets in the study of biological systems creates a need for new and more efficient methods of data management and analysis. Thus, it is widely expected that the BRAIN initiative, which will provide substantial resources to advance our ability to record simultaneously from many neurons, will also have a significant \"computational\" component related to the storage, handling, and analysis of the huge bodies of data that will be generated. It is much less widely appreciated that making sense of the collective behavior in systems with many interacting degrees of freedom requires theory, not just analysis. The goal of this work is to develop such a theoretical framework.<br /><br /><br />The PI's collaborators are using multi-electrode arrays to monitor activity in populations of ganglion cells in the vertebrate retina, as well as optical methods to monitor activity in mammalian cortical and hippocampal circuits, and in the whole brain of the nematode C elegans. The PI will use maximum entropy ideas, which have had some success in such problems, to build models of the joint distribution of activity across the hundreds of neurons in each of these experiments. The entropy of this distribution determines the capacity of the network to carry information, and the geometry of the distribution captures intuition about network function. Beyond exploring the distribution of activity, the PI will construct a \"thermodynamics\" for these networks that will allow to place real networks in a phase diagram of possible networks. Finally, the PI will turn to dynamical aspects of network behavior, focusing on the encoding of predictive information. The PI's research is well integrated with teaching at the graduate and undergraduate level, and there will be a special effort to create a \"current topics\" course that brings issues at the interface of physics and biology to the attention of a broader group of students. In addition, the PI is engaged is a series of public outreach efforts, which will culminate in a book for a general audience.","FID":6}},{"geometry":{"x":-1.3051471809030788E7,"y":3884523.6801554933,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Closed Loop Computing in the Brainstem","Organization":"University of California-San Diego","City":"La Jolla","State":"CA","Abstract":"Neuronal circuits in the brainstem are at the \"front-end\" of sensorimotor loops that underlie behavior and cognitive processing. They control life-sustaining functions that include breathing, movement and balance, sniffing, chewing, suckling in neonates, and, in rodents, whisking. These circuits further drive active sensation through taste, smell, balance, and touch. In this project the PI will delimit the circuits that control different motor actions and show how behaviors emerge as an assembly of these actions.<br /><br />The \"front-end\" circuits of orofacial processing control life-sustaining functions that include breathing, movement and balance, sniffing, chewing, suckling in neonates, whisking in rodents, and vocalization. The functions, some of which share common muscles, must occur without compromising the patency of the airway. The control structure is not understood and nontrivial and it will serve as a model for the control and coordination of concurrent neuronal processes at any level in the nervous system. The application of control theory to nervous systems was proposed by the Cyberneticists of the 1940s to 1960s. These prescient notions were stymied by a lack of experimental tools to identify and control the circuits that underlie behavior. We now have sufficient tools to map brainstem circuits and the PI will exploit the tools of engineering and physics to gain insight into fundamental sensorimotor processes. The technical aspect of the the PI's approach involves the introduction of molecular tools based on the expression of lineage factors and constitutive proteins to identify brainstem neurons and track tracing tools based on trans-synaptic viruses to reveal connectivity The project will contribute to the education and the training of future multidisciplinary scientists through research-based education of undergraduate and graduate students. Technical aspects of work will be broadly disseminated through the involvement of the PIs and colleagues in graduate and post-graduate summer schools.","FID":7}},{"geometry":{"x":-1.3051624683087356E7,"y":3885096.957867633,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: A Proposed New Principle of Brain Organization","Organization":"University of California-San Diego","City":"La Jolla","State":"CA","Abstract":"Most brain areas (like visual or motor cortex) are believed to have a map in which neuron location is related to the type of information that neuron processes. For example, in the visual cortex, neurons process information about a part of the visual world that is closely related to their map location in the brain. The idea explored in this project is that some important brain areas have an antimap, rather than a map, in which the type of information conveyed by a neuron is not at all related to its location in the antimap. Instead, information is spread out over the antimap in a way that makes it possible to get all of the available information from a small collection of any neurons in the antimap, as long as a critical number of neurons is selected. The conceptual basis for this antimap idea comes from a new field of mathematics and computer science called \"compressed sensing\", and compressed sensing places strict limits on the possible ways brain areas can communicate if an antimap is to be formed. A goal of the project, then, is to discover if the evolutionarily ancient brain areas noted above conform to these limits. The reason for the brain to use antimaps is that they provide information in a format that can be used to collect arbitrary pieces of information into a single \"object\" through learning. The goal of this EAGER project is to explore the new idea about how information is represented in four evolutionarily ancient brain areas: hippocampus, cerebellum, olfactory cortex, and basal ganglia, present in all vertebrates. To achieve this goal the PI will search the literature on anatomical and physiological characteristics of inputs to these four areas (and sub-parts of them), and will compile quantitative neuroanatomical data that will permit a comparison of what is observed with what the idea predicts. The outcome will determine the extent to which this new idea is tenable and lead to understanding its possible implications for computations in the various brain areas. <br /><br />This work is, by its nature, interdisciplinary as it relies on ideas from neurobiology, mathematics and computer science, and on the methods of theoretical physics. If the idea of antimaps is correct, all vertebrate (and perhaps invertebrate) brains use them to solve a wide variety of computational problems. Furthermore, knowing how information is represented in the brain is fundamental to understanding how the brain works, and if this new idea is correct it will play an essential role in achieving the goals of the BRAIN initiative.","FID":8}},{"geometry":{"x":-7911318.527956123,"y":5215067.995893319,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"NSF EAGER: Initiative for Physics and Mathematics of Neural Systems","Organization":"Trustees of Boston University","City":"Boston","State":"MA","Abstract":"This project will foster collaborations between physicists, mathematicians and neuroscientists to generate theoretical frameworks and statistical tools to interpret genomic, anatomical and physiological data on brain function. A community of researchers will be built through development of a seminar series for discussions of problems in which the theoretical approaches of physics, mathematics and statistics can be brought to be bear on specific research questions regarding neural systems. In addition, a set of pilot projects will be funded to foster collaborations between mathematicians, physicists and neuroscientists. Specific pilot projects will use the techniques of theoretical physics to address problems of understanding large scale functional anatomical connectivity, with the objective of identifying constraints on the distance and pattern of inter-areal connectivity in the human brain. Pilot projects will also develop a theoretical framework for understanding neural activity on different time scales during behavior, with the objective of understanding the unifying neural principles underlying human memory behavior over time scales from seconds to minutes to hours. Pilot projects will also develop mathematical and statistical techniques to identify molecular networks underlying specific features of neural function, with the objective of identifying specific network modules in the prefrontal cortex. These pilot projects will provide example interactions that can be expanded to further build a community of interaction of physicists, mathematicians and neuroscientists. <br /><br />The maturation of scientific fields such as physics required the development of sophisticated theoretical frameworks to account for experimental phenomena at multiple different scales of analysis ranging from particle physics to condensed matter physics to astrophysics. The maturation of neuroscience as a field will require similarly sophisticated theoretical frameworks that effectively account for data at the different levels including the genomic, physiological and behavioral levels. Current theories of single neuron function have not yet been effectively extended to address physiological phenomena at the circuit and population level or the behavioral function of these network dynamics. The pilot projects in this grant will attempt to develop theoretical frameworks for addressing these multiple levels of analysis. The intellectual merit of the proposal will be the application of mathematical and statistical techniques to the interpretation of neuroscience data, including the development of theoretical models to account for existing data and to guide the design of future experiments. The field of neuroscience needs more extensive development of a theoretical framework for understanding the structure and function of neural systems at different levels, including genomic, physiological and behavioral. Successful interactions in the pilot projects could provide a model for further interaction of physicists, mathematicians, and neuroscientists throughout the field. More specifically, these pilot projects will provide a framework for development of new theories for analyzing the connectivity patterns of neural systems, the dynamics of brain function underlying behavior, and the molecular networks underlying these neural properties. The resources provided by this grant will serve to recruit additional mathematicians and physicists to address relevant questions concerning brain function.<br /><br />This project is being jointly supported by the Physics of Living Systems program in the Division of Physics and the Mathematical Biology program in the Division of Mathematical sciences.","FID":9}},{"geometry":{"x":-8898397.796008227,"y":4928624.0683508655,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"CRCNS US-Israel Research Proposal: Understanding single neuron computation by combining biophysical and statistical models","Organization":"Carnegie-Mellon University","City":"Pittsburgh","State":"PA","Abstract":"What make a neuron become active? This question, central to our understanding of brain processes, is both a biophysical question about underlying biological mechanisms, and a statistical question about the features of incoming stimuli to which a neuron responds. The overall goal of this project is to forge a link between the biological mechanisms of neuronal activity and the computational process by which neurons encode features of incoming stimuli. More specifically, this project seeks to understand the biological underpinnings of stimulus coding by neurons.<br /><br />Dynamical models of neurons that incorporate detailed information about the ion channels that these cells express provide a detailed, biophysical account of neuronal activity. These kinds of models have been used widely and can incorporate and constrain an impressive amount of biological detail. Unfortunately they provide little insight into the meaning of neuronal activity or into the kinds of computations and transformations of stimuli that neurons are performing. On the other hand, models derived from statistical approaches are able to capture the often-noisy and complex relationships between neural activity and the stimuli that a neuron receives. These models provide insight into how specific features of incoming stimuli are extracted and combined by populations of neurons. <br /><br />These approaches will be combined through collaboration of a team at Carnegie Mellon University (Urban and Kass) and one at Bar-Ilan University (Korngreen) with expertise in the application of statistical and biophysical models to single neuron data. The work will focus on two neuron types that have several important features in common. Olfactory bulb mitral cells and layer 5 neocortical pyramidal cells are two classes of large neurons that receive distinct sources of input inputs onto different divisions of their elaborate dendritic trees. To forge this connection between dynamic and statistical models, this project will develop detailed biophysical models using recently described methods and extend the framework of current statistical models to allow the interpretation of the functional consequences of ion channels and their localization on specific classes of inputs. Applying these improved methods, and examining the consequences of changing biophysical properties on the ability of neurons to robustly and effectively represent stimuli will generate a novel account of the linkage because biological mechanisms and single neuron computation. A companion project is being funded by the Israel Binational Science Foundation (BSF).","FID":10}},{"geometry":{"x":-1.243088026298594E7,"y":4899961.849144967,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"SBE: Small: The Force of Habit: Using fMRI to Explain Users' Habituation to Security Warnings","Organization":"Brigham Young University","City":"Provo","State":"UT","Abstract":"Warning messages are one of the last lines of defense in computer security, and are fundamental to users' security interactions with technology. Unfortunately, research shows that users routinely ignore security warnings. A key contributor to this disregard is habituation, the diminishing of attention due to frequent exposure. However, previous research examining habituation has done so only indirectly, by observing the influence of habituation on security behavior, rather than measuring habituation itself. This project uses neuroscience to open the \"black box\" of the brain to observe habituation as it occurs. By investigating how repetition suppression occurs in the brain, researchers can make a more precise approach to designing security warnings that are resistant to the effects of habituation.<br /><br />Specifically, functional magnetic resonance imaging (fMRI) is used to measure how neural activity in the visual processing centers of the brain sharply decrease with repeated exposure to warnings. This phenomenon, termed the repetition suppression effect, is directly antecedent to the process of habituation. This project aims to: (1) directly measure how habituation of security warnings occurs in the brain; (2) examine how habituation towards security warnings develops over time using a longitudinal design; and (3) use fMRI brain data to guide the design of polymorphic (dynamic) security warnings, as well as to empirically test their effectiveness compared with existing security warnings. The insights gained from this project have the potential to inform the design and evaluation of warnings that more effectively help users to respond to security threats.","FID":11}},{"geometry":{"x":-1.3167804866256345E7,"y":4032451.787059605,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Broadening Participation at the Computational and Systems Neuroscience Conference (Cosyne)","Organization":"University of Southern California","City":"Los Angeles","State":"CA","Abstract":"Remarkable progress in the understanding of the brain in recent years is due in part to the increasing role that theory and computational methods are playing in the design of experiments and interpretation of data. The annual Computational and Systems Neuroscience (Cosyne) conference promotes this process by providing an inclusive forum for the exchange of experimental and theoretical/computational approaches to problems in systems neuroscience. This purpose of this project is to broaden participation at the Cosyne meeting to include more individuals from under-represented groups through a continuing travel grant program targeting early-career scientists, and a new program of mentored travel awards for undergraduates. Both programs will be active for the 2015, 2016, and 2017 Cosyne meetings.","FID":12}},{"geometry":{"x":-1.3553002040968036E7,"y":4658206.617923487,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Brain evolution in the context of efficient resource extraction","Organization":"University of California-Davis","City":"Davis","State":"CA","Abstract":"The increasing of brain size is a defining feature of human evolutionary history. Because brain tissue is metabolically expensive, a central question about human origins is how our ancestors acquired the additional energy necessary to grow and maintain large brains. Current hypotheses focus on relatively recent behavioral changes, suggesting that meat-eating, food processing, or cooking may have increased diet quality and led to higher net energy gain. Brain expansion, however, is not restricted to the human lineage; it is an older and more general pattern across the primates. This suggests that a more fundamental process is responsible for the early stages of this energetically expensive brain expansion. One recent suggestion is that primates possess a sophisticated 'mental tool-kit' that enables them to extract resources from their habitat more efficiently than other species. It has been impossible to adequately evaluate this hypothesis, however, because we lack the critical comparative ecological data.<br /><br />The aim of this research is to test if primates forage 'smarter' or 'better' than other fruit-eating species, both facilitated by, and energetically supporting, their larger brains. The movements of six frugivorous mammals will be recorded using GPS tracking during an ecologically 'simple' time of year when a single, major fruit source (Dipteryx oleifera) is available that is shared by these species. By comparing how distantly related, but ecologically similar, species living in the same habitat find food, this project will test if 1) patterns of movement and food exploitation are consistent with species-level differences in what animals know about their habitat, and 2) if complex foraging strategies lead to more efficient resource acquisition. If these are supported, the research will provide evidence to support a 'positive feedback loop model' for primate cognitive evolution: Increased brain-size (arising from social and/or ecological pressures) leads to enhanced cognitive abilities that improve food-gathering efficiency, while this, in turn, generates an energetic surplus that potentiates the growth of a bigger brain. If cognitive abilities and foraging success do not differ among species, then alternatively, these results will challenge widespread assumptions about the relative sophistication of primate foraging behavior, and force a reexamination of how the early stages of primate brain expansion were energetically financed.<br /><br />To broaden the impact of these results, researchers will create online videos about how this study contributes to our understanding of evolution of the human brain. In addition, live web-cast updates from the field will be presented to museum visitors through collaboration with the North Carolina Museum of Natural Sciences, fostering understanding of science and the research process. Outreach activities also will include creation of opportunities for Panamanian school children to attend training seminars, gain hands-on experience with scientific research, and meet and interact with both Panamanian and US scientists, fostering science education and appreciation. Finally, the project will enhance education of future scientists through training of both US and Panamanian undergraduate students from backgrounds that have traditionally been underrepresented in the field of biological anthropology.","FID":13}},{"geometry":{"x":-9406532.110919401,"y":4586292.240055944,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Collaborative Research: Skeletal muscle constraint on relative brain size","Organization":"University of Kentucky Research Foundation","City":"Lexington","State":"KY","Abstract":"The growth and maintenance of the brain require substantial investments of energy, most especially for organisms which have evolved very large and complex brains. One of the most defining characteristics for the human species and the other primates is large brain size relative to body size. Yet, despite having larger brains than most other mammals, human and nonhuman primates do not show an increase in their basal metabolic rate (a measure of energy utilization by the body) compared to other mammals, raising the question of how the high energetic cost of such large brains is met. This trend suggests that there is an energetic trade-off with another energy-demanding tissue in the body when brain size increases; if we are not using more energy overall, then energy that could be invested in another part of our body is instead likely being utilized to fuel our large brains. Preliminary research shows that primates have low muscle mass when compared to other animals, and humans, who have the most notable increase in brain size, show a 50% reduction in overall muscle mass when compared with other mammals. This research therefore tests the hypothesis that skeletal muscle is in direct competition with the brain for glucose and oxygen, such that the high energetic demands of large brain size are met through constraining muscle mass, constituting an energetic tradeoff between skeletal muscle growth and maintenance, and brain growth and maintenance. <br /><br />If the brain does constrain muscle mass, then 1)larger brains should be associated with decreased skeletal muscle mass; 2)the percentage of type I muscle fibers (a type of muscle cell that uses energy [glucose, a type of sugar] in a similar fashion to brain cells) should show a relative decrease in relation to larger brain size; and 3)muscle mass development should be suppressed until brain growth is complete, and once complete, there should be an increase in muscle mass development. To test these predictions, muscle tissue samples will be collected from a diverse array of primate specimens, comprising a range of brain sizes and representing all developmental stages. The generated muscle energy use profiles for each species will then be analyzed in relation to variation in brain size, with the results applied to understanding the interaction between brain size and evolved metabolic strategies. <br /><br />Reducing muscle mass may have predisposed primates such as humans to certain metabolic disorders (e.g., type 2 diabetes); thus, understanding if there is such a constraint has important health implications. Ultimately, the data collected can be incorporated into studies of growth and development, as well as biomechanics, and the results may encourage development of biomedical gene therapies. The research also will provide a rich database for scientists in other disciplines focusing on animal anatomy and physiology, facilitating and expanding future research. The collaborative project brings together international researchers, and will support the training of multiple undergraduate and graduate students from three US universities. As two of these universities are in EPSCoR states, and one is a historically minority-serving institution, the project will foster research advancement for underserved and underrepresented populations.","FID":14}},{"geometry":{"x":-9021929.058730844,"y":4028643.8698134874,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Collaborative Research: Skeletal muscle constraint on relative brain size","Organization":"University of South Carolina at Columbia","City":"Columbia","State":"SC","Abstract":"The growth and maintenance of the brain require substantial investments of energy, most especially for organisms which have evolved very large and complex brains. One of the most defining characteristics for the human species and the other primates is large brain size relative to body size. Yet, despite having larger brains than most other mammals, human and nonhuman primates do not show an increase in their basal metabolic rate (a measure of energy utilization by the body) compared to other mammals, raising the question of how the high energetic cost of such large brains is met. This trend suggests that there is an energetic trade-off with another energy-demanding tissue in the body when brain size increases; if we are not using more energy overall, then energy that could be invested in another part of our body is instead likely being utilized to fuel our large brains. Preliminary research shows that primates have low muscle mass when compared to other animals, and humans, who have the most notable increase in brain size, show a 50% reduction in overall muscle mass when compared with other mammals. This research therefore tests the hypothesis that skeletal muscle is in direct competition with the brain for glucose and oxygen, such that the high energetic demands of large brain size are met through constraining muscle mass, constituting an energetic tradeoff between skeletal muscle growth and maintenance, and brain growth and maintenance. <br /><br />If the brain does constrain muscle mass, then 1)larger brains should be associated with decreased skeletal muscle mass; 2)the percentage of type I muscle fibers (a type of muscle cell that uses energy [glucose, a type of sugar] in a similar fashion to brain cells) should show a relative decrease in relation to larger brain size; and 3)muscle mass development should be suppressed until brain growth is complete, and once complete, there should be an increase in muscle mass development. To test these predictions, muscle tissue samples will be collected from a diverse array of primate specimens, comprising a range of brain sizes and representing all developmental stages. The generated muscle energy use profiles for each species will then be analyzed in relation to variation in brain size, with the results applied to understanding the interaction between brain size and evolved metabolic strategies. <br /><br />Reducing muscle mass may have predisposed primates such as humans to certain metabolic disorders (e.g., type 2 diabetes); thus, understanding if there is such a constraint has important health implications. Ultimately, the data collected can be incorporated into studies of growth and development, as well as biomechanics, and the results may encourage development of biomedical gene therapies. The research also will provide a rich database for scientists in other disciplines focusing on animal anatomy and physiology, facilitating and expanding future research. The collaborative project brings together international researchers, and will support the training of multiple undergraduate and graduate students from three US universities. As two of these universities are in EPSCoR states, and one is a historically minority-serving institution, the project will foster research advancement for underserved and underrepresented populations.","FID":15}},{"geometry":{"x":-8784545.853133647,"y":4297240.036331692,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Solving the Code of Olfaction Using Nano-Robot Switchable Odorants","Organization":"Duke University","City":"Durham","State":"NC","Abstract":"The sense of small (olfaction) holds in it a major mystery: No scientist or perfumer can look at the structure of a novel molecule and predict its odor or molecular structure. This project aims to develop molecules that bind to individual olfactory receptors in the nose and thereby help solve the code by which odors result in odor perception. The proposed approach has broad implications and applications: It may pave the path towards the introduction of odor into everyday devices. The idea of odor-emitting televisions, computer game boxes, cell-phones, etc, has existed for some time. However, this goal remains unattained, mostly for \"simple\" technical reasons: Even if one successfully generates an odor-emitting device, what does one then do with the emitted odor? For example, a car-racing computer game may emit the smell of burning rubber tires, but how does one then evacuate the smell of burning rubber from the room? Moreover, given that odors linger, how can one rapidly switch from one odor to the next? The technology proposed here may solve these problems because it will entail particles that are odorless, yet take on a given odor as a function of rapidly-switchable externally applied fields. If successful, the proposed mechanism will drive a revolution of odor devices. Further, the \"switchable chemical\" approach will be extendable to other receptors in the brain, and can be applied towards asking basic questions concerning emotion, sensorimotor-coordination, memory and learning, as well as developing potential novel therapies for diseases associated with receptor signaling failure. <br /><br />To develop a path towards solving the combinatorial code of olfaction, the Bachelet lab will design DNA strands called aptamers that assume a 3D structure that will specifically bind to a single type of olfactory receptor and induce signal transduction. These DNA-based \"artificial odorants\" will be tagged with a nanoparticle that changes its conformation in response to an external electromagnetic field. The product will be artificial odorants that are externally switchable in vivo. The Matsunami lab will use tissue culture cells expressing olfactory receptors to validate the function and selectivity of these switchable nano-robot odorants. The Sobel lab will then apply these artificial odorants to the human olfactory system, and measure perception and neural activity following switching the artificial odor on and off. This three-level approach will allow closure of the loop from receptor to perception, and potentially answer in this way what remains a fundamental question in olfaction.","FID":16}},{"geometry":{"x":-7914395.538109749,"y":5216808.545023563,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Functional dynamics of whole brain activity, behavior, and development from birth to adulthood","Organization":"Harvard University","City":"Cambridge","State":"MA","Abstract":"From birth to adulthood, the brain and nervous system continuously expand and develop to keep up with the growing body. Neurons and connections must constantly be added or changed for any animal, including humans, to gain new behaviors or retain old ones. This project is to develop and apply technology to monitor brain and behavior from birth to adulthood of the roundworm C. elegans, an important and widely studied model for neuroscience. A controlled environment will be created where individual animals are born, roam freely, and grow to adulthood while a microscope continuously scans the activity patterns of every neuron in the worm's nervous system. Because of their rapid maturation (<br /><br />A system will be developed-- a motorized, rotating agar-coated ball-- upon which a nematode can freely move without interruption as it feeds, grows, molts through four larval stages, and becomes an adult. Throughout the nematode's life, the system will record the activity of the entire nervous system visualized throughout its optically transparent body using a confocal microscope that achieves video-rate volumetric recording. These experiments will provide unprecedented datasets that describe the behavioral life history of an individual animal in temporal correlation with whole brain activity patterns. Comparison of these rich datasets between wild-type animals and informative mutants will allow dissection of a wide range of interconnected and shared processes in neurodevelopment, regulation, learning, and memory. For example, understanding the developmental progression of the motor circuit will be achieved by obtaining circuit-wide measurements that describe how the 20-neuron motor circuit that drives the forward and backward movements of the 0.1-mm long juvenile worm is expanded into the 80-neuron motor circuit that drives the same movements of the 1-mm long adult. These studies will illuminate system-wide changes in the nervous system as it dynamically keeps up with animal growth.","FID":17}},{"geometry":{"x":-8575158.410835912,"y":4705980.21401279,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Collaborative Research: Skeletal muscle constraint on relative brain size","Organization":"Howard University","City":"Washington","State":"DC","Abstract":"The growth and maintenance of the brain require substantial investments of energy, most especially for organisms which have evolved very large and complex brains. One of the most defining characteristics for the human species and the other primates is large brain size relative to body size. Yet, despite having larger brains than most other mammals, human and nonhuman primates do not show an increase in their basal metabolic rate (a measure of energy utilization by the body) compared to other mammals, raising the question of how the high energetic cost of such large brains is met. This trend suggests that there is an energetic trade-off with another energy-demanding tissue in the body when brain size increases; if we are not using more energy overall, then energy that could be invested in another part of our body is instead likely being utilized to fuel our large brains. Preliminary research shows that primates have low muscle mass when compared to other animals, and humans, who have the most notable increase in brain size, show a 50% reduction in overall muscle mass when compared with other mammals. This research therefore tests the hypothesis that skeletal muscle is in direct competition with the brain for glucose and oxygen, such that the high energetic demands of large brain size are met through constraining muscle mass, constituting an energetic tradeoff between skeletal muscle growth and maintenance, and brain growth and maintenance. <br /><br />If the brain does constrain muscle mass, then 1)larger brains should be associated with decreased skeletal muscle mass; 2)the percentage of type I muscle fibers (a type of muscle cell that uses energy [glucose, a type of sugar] in a similar fashion to brain cells) should show a relative decrease in relation to larger brain size; and 3)muscle mass development should be suppressed until brain growth is complete, and once complete, there should be an increase in muscle mass development. To test these predictions, muscle tissue samples will be collected from a diverse array of primate specimens, comprising a range of brain sizes and representing all developmental stages. The generated muscle energy use profiles for each species will then be analyzed in relation to variation in brain size, with the results applied to understanding the interaction between brain size and evolved metabolic strategies. <br /><br />Reducing muscle mass may have predisposed primates such as humans to certain metabolic disorders (e.g., type 2 diabetes); thus, understanding if there is such a constraint has important health implications. Ultimately, the data collected can be incorporated into studies of growth and development, as well as biomechanics, and the results may encourage development of biomedical gene therapies. The research also will provide a rich database for scientists in other disciplines focusing on animal anatomy and physiology, facilitating and expanding future research. The collaborative project brings together international researchers, and will support the training of multiple undergraduate and graduate students from three US universities. As two of these universities are in EPSCoR states, and one is a historically minority-serving institution, the project will foster research advancement for underserved and underrepresented populations.","FID":18}},{"geometry":{"x":-7913669.38634104,"y":5215088.711887149,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"A Center for Brains, Minds and Machines: the Science and the Technology of Intelligence","Organization":"Massachusetts Institute of Technology","City":"Cambridge","State":"MA","Abstract":"Today's AI technologies, such as Watson, Siri and MobilEye, are impressive yet still confined to a single domain or task. Imagine how truly intelligent systems --- systems that actually understand their world --- could change our world. The work of scientists and engineers could be amplified to help solve the world's most pressing technical problems. Education, healthcare and manufacturing could be transformed. Mental health could be understood on a deeper level, leading in turn to more effective treatments of brain disorders. These accomplishments will take decades. The proposed Center for Brains, Minds, and Machines (CBMM) will enable the kind of research needed to ultimately achieve such ambitious goals. The vision of the Center is of a world where intelligence, and how it emerges from brain activity, is truly understood. A successful research plan for realizing this vision requires four main areas of inquiry and integrated work across all four guided by a unifying theoretical foundation. First, understanding intelligence requires discovering how it develops from the interplay of learning and innate structure. Second, understanding the physical machinery of intelligence requires analyzing brains across multiple levels of analysis, from neural circuits to large-scale brain architecture. Third, intelligence goes beyond the narrow expertise of chess or Jeopardy-playing computers, bridging several domains including vision, planning, action, social interactions, and language. Finally, intelligence emerges from the interactions among individuals ? it is the product of social interactions. Therefore, the research of the Center engages four major research thrusts (Reverse Engineering the Infant Mind, Neuronal Circuits Underlying Intelligence, Integrating Intelligence, and Social Intelligence) with interlocking teams and working groups, and a common theoretical, mathematical, and computational platform (Enabling Theory).<br /><br />The intellectual merit of the Center is its focus on elucidating the mechanisms and architecture of intelligence in the most intelligent system known: the human brain. Success in this project will ultimately enable us to understand ourselves better, to produce smarter machines, and perhaps even to make ourselves smarter. The Center's potential legacy of a deep understanding of intelligence, and the ability to engineer it, is tantalizing and timeless. It includes the creation of a community of researchers by programs such as an intensive summer school, technical workshops and online courses that will train the next generation of scientists and engineers in an emerging new field -- the Science and Engineering of Intelligence. This new field will catalyze continuing progress in and cross-fertilization between computer science, math and statistics, robotics, neuroscience, and cognitive science. Sitting between science and engineering, it will attract growing interest from the best students at all levels. The broader impact of the Center program could be to revolutionize K-12, and also 0-K, and 12-life with a deeper understanding of the process of learning. The ability to build more human-like intelligence in machines will transform our productivity, enabling robots to care for the aged, drive our cars, and help with small-business manufacturing. The Center team is composed of over 23 investigators, many having already made significant accomplishments in multiple research areas relevant to the science and the technology of intelligence. The Center team has a mix of junior and senior researchers, bringing expertise in Computer Science, Neuroscience, Cognitive Science and Mathematics. The institutional partners include nine institutions (MIT, Harvard, Cornell, Rockefeller, UCLA, Stanford, The Allen Institute, Wellesley, Howard, Hunter and the University of Puerto Rico), three of which have significant underrepresented student populations. The academic institutions are complemented by the Center's industrial partners (Microsoft, IBM, Google, DeepMind, Orcam, MobilEye, Willow Garage, RethinkRobotics, Boston Dynamics) and by world-renowned researchers at international institutions (Max Planck Institute, The Weizmann Institute, Italian Institute of Technology, The Hebrew University).","FID":19}},{"geometry":{"x":-1.1719631223595237E7,"y":4868230.181147659,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Syntax-Semantics Interaction During Sentence Comprehension: An Individual Differences Approach","Organization":"University of Colorado at Boulder","City":"Boulder","State":"CO","Abstract":"The ability to comprehend language is a hallmark of human intelligence. Although this ability seems to come effortlessly to neurologically normal adults, such ease belies a complex underlying network of neural processes. A major challenge in investigating the neural mechanisms of language comprehension is that people may not all process language in exactly the same way. People may vary substantially, for example, in the ease with which they can recognize words and in their abilities to hold in mind information about the preceding words and sentences. Given such individual differences, the mechanisms of language processing can be obscured if researchers adopt the common neuroimaging practice of averaging together brain activity from different people who have experienced the same stimuli (for example, the same word). With support from the National Science Foundation, Dr. Albert Kim and his colleague Dr. Akira Miyake will investigate the neural mechanisms of language comprehension with a focus on systematic differences between individuals. . Dr. Kim and Dr. Miyake will record brain electrical activity using electroencephalography (EEG) from the scalps of participants who are reading sentences, measuring event related potentials (ERPs) for each word in the sentences. They will incorporate recent advances in application of blind source separation (BSS) algorithm into this research to enable separation of fast brain electrical signals from different brain regions and enable characterization of individual differences in the neurobiology of language processing in ways that cannot be provided by fMRI based brain imaging. <br /><br />Developmental disorders of language comprehension impede scholastic and professional success, and acquired language comprehension disorders, such as those following stroke, can be fundamentally debilitating. Thus, understanding the basic mechanisms of language processing is likely to be relevant to the diagnosis and treatment of disordered language. Because of the novelty of simultaneously measuring and comparing multiple measures of individual differences in language processes, this work has the potential to transform current research practices in the field. Dr. Kim and Dr. Miyake will maximize the broader impact of the work by organizing special journal issues in appropriate outlets and special workshops within national and international conferences. The goal of these special issues and workshops will be to assemble research in various areas in cognitive neuroscience (e.g., language, memory, attention, decision making) that illustrates the theoretical importance and viability of integrating individual differences analyses, neurocognitive theories, and modern analysis methods. Finally, because the proposed research involves multiple research methods and approaches, it will provide exceptionally rich training opportunities to the graduate students and undergraduate students who will be working on the project.","FID":20}},{"geometry":{"x":-8042491.176171815,"y":5421038.650811278,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"CRCNS US-German Data Sharing: DataGit - converging catalogues, warehouses, and deployment logistics into a federated 'data distribution'","Organization":"Dartmouth College","City":"Hanover","State":"NH","Abstract":"Contemporary neuroscience is heavily data-driven, but today's data management technologies and sharing practices fall at least a decade behind software ecosystem counterparts. Distributed version control systems, such as Git, facilitate collaborative software development, and turnkey distributions, like NeuroDebian, free researchers from tedious and unreliable maintenance tasks. Likewise, neuroscientists will need to incorporate recent technological developments to access, manage, and contribute back to the ever growing array of scientific data more efficiently. Making a rich collection of disjoint datasets available through a simple unified interface can transcend limitations of individual studies and revolutionize how scientific data are managed, distributed, and shared across all fields of science. With support from the National Science Foundation, Dr. Yaroslav O. Halchenko of Dartmouth College, along with Dr. Michael Hanke of the University of Magdeburg (Germany), will develop DataGit, a suite of data distribution tools. DataGit will employ software for data tracking and deployment logistics to unify access to many existing neuroimaging data hosting portals, such as crcns.org, openfmri.org and humanconnectome.org. DataGit will make it easy to access existing data and to share new or derived data with full support for distributed version control, data integrity protection and authenticated access to original data hosting.<br /><br />Making data management as easy and as versatile as source code management will further the efforts toward open and fully reproducible science. Uniform access to federated collections of data will promote the visibility and accessibility of neuroscientific data inside and outside the field, far beyond the scope of any individual data-sharing effort. The benefits from the proposed developments will translate directly to educators' aims in the classroom. Through integration with software distributions, uniform access to software elements and datasets for online training materials will enable educators to teach not only from textbooks but also through hands-on replication of state-of-the-art original publications. In addition, giving any researcher the ability to easily deploy complex heterogeneous analysis pipelines will be instrumental in translating the achievements of flagship efforts, such as the Human Connectome Project, into accessible tools for clinical applications. Consequently, even more researchers will be able to tackle even larger challenges to benefit society by improving our understanding of the human brain.<br /><br />A companion project is being funded by the German Ministry of Education and Research (BMBF).","FID":21}},{"geometry":{"x":-8235453.749037165,"y":4973004.209568427,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Linking Real-Time Categorization Dynamics to Real-world Social Dynamics","Organization":"New York University","City":"New York","State":"NY","Abstract":"A seminal area of social psychological research is in understanding the root causes of stereotyping and discrimination. How might disparities in hiring, pay, and promotions arise? Disparities could stem, in part, from perceived incongruities between an individual and a prototypical expectation for a particular role, even at the level of facial features. When a target's features fit others' expectations or prototypes, their perceived suitability for the role could be enhanced. This might occur when an individual with more feminine features applies for a stereotypically feminine job, e.g., child care provider, or an individual with more prototypically Asian features seeks entry into a field stereotypically associated with Asian-Americans, e.g., a science/technology/engineering/math (STEM) graduate program. Individuals whose subtle facial features deviate from these expectations may have to struggle to demonstrate their suitability for such positions over and above others who are more prototypical. The proposed research will examine whether the cognitive mechanisms underlying the basic ways we see, understand, and categorize other people influence such real-world social behaviors. In other words, how can biases in the process of categorizing others lead to downstream outcomes of interpersonal and societal significance, such as hiring and admission decisions and voting behavior? <br /><br />Previous work by the investigator Jonathan Freeman (New York University) and colleagues has shown that the process of categorizing individuals is dynamic and evolves over hundreds of milliseconds. For instance, cues specifying gender, race, and age are processed early in the perceptual stream, but as more information accumulates, initial tentative perceptions are gradually sharpened until a final categorization that best integrates all cues stabilizes. Mouse-tracking software developed by the investigator can track this process in real-time, determining how multiple conflicting categories (e.g., \"white\" and \"black\") may be activated and resolved while an individual categorizes another person. This technique will be used to examine how individuals whose facial features are slightly atypical for their gender or race may trigger competing social categories (e.g., \"male\" and \"female\"), and how such cognitive competition may predict downstream social behavior. The proposed research will first examine processes underlying categorization when competing social categories are activated, and then extend this foundational knowledge to several societally-relevant outcomes, including how categorization on the basis of gender and/or racial cues lead to different hiring and admission decisions. Finally, the neural basis of these categorization decisions will be examined, to test how cognitive and neural dynamics jointly predict important behaviors. Together, this research has the potential to make transformative advances in social psychology by establishing links between real-time cognitive and real-world social dynamics, using cutting-edge methodologies to bridge multiple time scales in person perception. The findings will expose the processes underlying appearance-based stereotyping and their links to social behavior, and have numerous implications for reducing the effects of discrimination in the real world.","FID":22}},{"geometry":{"x":-1.0382433667143734E7,"y":5615927.74503841,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: High-resolution multimodal acousto-electromagnetic neuroimaging of brain activity","Organization":"University of Minnesota-Twin Cities","City":"Minneapolis","State":"MN","Abstract":"PI: He, Bin <br />Proposal: 1450956 <br />Title: BRAIN EAGER: High-resolution multimodal acousto-electromagnetic neuroimaging of brain activity <br /><br />Significance <br />Brain activity resulting from neuronal excitation is distributed over the 3-dimensional volume and evolves in time. There is a strong need to map the spatio-temporal distributions of brain activation noninvasively. The proposed project aims at developing a groundbreaking technology for neuroimaging of brain activity with high resolution in both space and time. The successful completion of the proposed exploratory project may lead to a transformative neuroimaging modality that would change the practice of functional neuroimaging and offer an extremely desirable high spatio-temporal resolution neuroimaging capability to noninvasively map dynamic neural information processing within the brain at neural circuits level. Such capability will have the potential to transform the current state-of-art that neuroimaging is carried out using separate modalities that can map brain activity either with high spatial or high temporal resolution, but unable to map dynamic brain activation with both high spatial resolution and high temporal resolution. This is of significant impact to human brain mapping, a grand challenge in the BRAIN Initiative. <br /><br />Technical Description <br />The PIs propose to develop a novel hybrid multimodal neuroimaging technology \"acousto-electromagnetic neuroimaging\" by fully integrating focused ultrasound with electromagnetic sensing and imaging for mapping dynamic brain activation. The proposed imaging technology has the potential to achieve millimeter spatial resolution and millisecond temporal resolution in a single hybrid neuroimaging system for mapping brain activation noninvasively in subjects throughout the lifespan. The central hypothesis is that using focused ultrasound modulation and electromagnetic sensing and source imaging, the PIs will be able to noninvasively detect and image dynamic brain activation and function at neural circuits level in the brain. The specific aims of the proposed project are as follows. Aim 1: Test the proposed acousto-electric neuroimaging in a rat model. In this aim, the investigators will use focused ultrasound to modulate regional neural activity and record the induced electrophysiological signals using an electrode-array. The investigators will decode the neural signals from ultrasound modulated electrical measurements and reconstruct the neural activation to test the hypothesis that the proposed imaging will reveal high spatio-temporal pattern of neural activation. Aim 2: Test the proposed acousto-magnetic neuroimaging in a rat model. In this aim, the investigators will use focused ultrasound to modulate regional neural activity and record the induced electrophysiological signals using a spintronic magnetic sensor array. They will decode the neural signals from ultrasound modulated magnetic measurements and reconstruct the neural activation to test the hypothesis that the proposed imaging will reveal neural activation at a high spatio-temporal pattern.","FID":23}},{"geometry":{"x":-1.062171270280154E7,"y":3468973.4808241343,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Flashes of insight: Revealing dynamic mental models during rodent virtual reality foraging","Organization":"Baylor College of Medicine","City":"Houston","State":"TX","Abstract":"A primary goal of neuroscience is to understand how the brain works-- not in artificial lab tasks, but when using its full capabilities to thrive in the rigors of the natural environment. Neuroscience has made enormous progress by examining how the brain performs simplified tasks, but these tasks do not expose the richly adaptive dynamics that the brain must use in a changing world. Therefore, the current neuroscientific understanding of the brain is missing fundamental ingredients. The current project begins to fill this gap, providing a new paradigm for the conduct of behavioral neuroscience and offering an unprecedented opportunity to observe the neural computations that solve a complex natural task. Team members will record activity of many neurons in multiple areas of a mouse brain while the mouse is foraging in a virtual reality environment, and develop mathematical models to make sense of the complex data. This research will thereby provide a unique training opportunity for undergraduate and graduate students in both computational and experimental neuroscience. The project results will be widely disseminated by sharing data, computational models, and analysis techniques with the neuroscience community through public data repositories, so conclusions can be replicated and extended. This research will thereby advance society?s goals of understanding the biology of healthy and disordered brains, with the ultimate hope of repairing neurological problems.<br /><br /> Experimenters will train mice to forage in a virtual reality environment, while recording activity from many neurons in four brain areas involved in vision and navigation: visual cortex, entorhinal cortex, posterior parietal cortex and hippocampus. State-of-the-art analysis techniques will be used to describe the mouse's behavior, and to discover neural representations of the internal models that express the animal's beliefs about things that cannot be observed directly in sense data. Finally, the project will uncover how neural representations of critical task variables are communicated and transformed across brain areas, guided by the hidden variable dynamics of the behavioral model. Together, these experiments, theory, and analysis will provide an unprecedented, system-wide understanding of neural computation, ranging from the scale of individual neurons up to a multi-region system. A key quality of the approach is the pervasive influence of theory, both in structuring experiments and dictating analyses. Since the great strength of the human brain is its ability to comprehend the hidden structure in the world, this approach takes an essential step toward unraveling the mysteries of cognition.","FID":24}},{"geometry":{"x":-1.0775214548517128E7,"y":3865894.1603807607,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Tagging the Genetic, Synaptic, and Network Origins of Learning from Social Experiences","Organization":"University of Texas Southwestern Medical Center at Dallas","City":"Dallas","State":"TX","Abstract":"How we learn from social experiences and during social interactions is poorly understood, but it is thought to involve intricate changes to nerve cells in the brain and the connections between these cells. Cells involved in social learning are intermingled and intertwined with cells that may have completely different functions. Because of this complexity, identifying and studying the specific cells and networks involved in social learning remain a major challenge, and new methods are required to address this needle-in-a-hay-stack problem. This research will build a new set of genetic tools that allow researchers to mark cells in the brains of mice and zebra finches that are specifically involved in learning during social interactions, and will apply cutting-edge imaging, physiological, and genetic methods to dissect how the marked cells change during learning. This research is of fundamental importance because it will shed light on the brain mechanisms involved in social learning and build a new set of genetic tools that can be used by the scientific community to study brain mechanisms involved in learning and memory. The research also is of importance because developmental disorders and head injuries can severely compromise circuits in the brain and individuals' ability to learn from social encounters and navigate complex social interactions. The tools and methodologies developed in this research will be made freely available to other scientists through the world-wide web (http://www.utsouthwestern.edu/education/medical-school/departments/neuroscience/index.html) and through the Addgene public repository (http://www.addgene.org/). Funding for this research will also be used to educate and train young scientists in novel genetic, molecular, imaging and behavioral methodologies. <br /><br />The proposed research will identify neuronal mechanisms involved in social learning from olfactory and auditory cues in mice and zebra finches, respectively. The proposal takes a highly interdisciplinary, collaborative approach involving four independent laboratories. The researchers will fluorescently \"tag\" neurons in mice and zebra finches that are selectively activated by olfactory and auditory social experiences using novel genetic strategies and viral tools that leverage the immediate-early gene c-Fos. Within brain regions of interest (olfactory and vocal learning circuits), these viral tools will differentially label neuronal populations depending on cellular activity and the specific social cues animals experience. In vivo Ca2+ imaging will be used to identify and map populations of neurons involved in processing and learning from social encounters. Novel optical methods will be used to map synaptic connectivity among tagged neuronal populations in vivo. Electrophysiological and transcriptomic analyses will be used to identify physiological and genetic factors unique to each tagged population, and identify neural subtypes and subpopulations responsible for social learning. These combined approaches will help reveal the network-level plasticity induced by social experiences. This collaborative, high-risk/high-impact research will generate novel in vivo molecular tools that allow fine and selective dissection of the network components of social learning.","FID":25}},{"geometry":{"x":-8308837.609712486,"y":4917523.3457446685,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Closing the Loop on Social Behaviors, From Mathematical Models to Neural Circuit Dynamics","Organization":"Princeton University","City":"Princeton","State":"NJ","Abstract":"Animals, from insects to humans, are inherently social, and brains have evolved to be most sensitive to sensory cues that carry social information (for example, speech sounds or pheromones). Very little is known regarding how animal brains process information in the context of social interactions. This proposal seeks to address this complex issue by focusing on the relatively simple nervous system of the fruit fly Drosophila, and takes advantage of the wealth of tools available in this system to dissect the mechanisms underlying social behaviors. The three principal investigators (Murthy, Shaevitz, and Bialek) are experts with behavioral analysis, theory/modeling, and neural circuit analysis, and will use several new methods to study courtship, a robust social behavior that has been shown to involve a complex interaction of a male and a female. This work will not only uncover the mechanism by which sensory inputs and internal states interact to generate behavior, but also benefit studies of disorders (e.g., autism spectrum) that impact the social brain. The research project is complemented by outreach efforts targeted at educating undergraduates, and in particular young women, in modern methods in computational neuroscience. <br /><br />Animals, from insects to humans, spend a majority of their time engaged in social behaviors, and brains have evolved to be most sensitive to these dynamics and timescales, as they are important for survival. Social interactions involve both sensory perception (detecting cues generated by another individual) and coordinating motor outputs (to generate social behaviors). Most studies examine sensory and motor pathways in an \"open loop\" framework; however, social interactions are inherently \"closed loop\", as data gathered through the senses of each individual is profoundly shaped by his/her own actions and those of the other individual. With new methods and new theoretical frameworks, this proposal aims to solve the closed loop aspect of sensory perception between animals using the fruit fly Drosophila melanogaster as a model system. The investigators have pioneered several new methods to facilitate these studies and are experts with behavioral analysis, theory/modeling, and neural circuit analysis. They will combine unbiased behavioral quantification, whole-brain imaging in behaving animals, controlled sensory stimuli, and theoretical modeling to uncover the neural circuit dynamics underlying social behaviors and decision-making. A detailed analysis of the simultaneous behaviors of two courting flies will lead to the first rigorous and quantitative analysis of the dynamic sensory cues and interactions between individuals that shape social behaviors. Theoretical work on these data will reveal the dynamic neural computations that must be active during courtship. Finally, neural circuit recordings in animals engaged in closed loop fictive social interactions will be used to link brain activity to specific courtship behaviors and decisions.","FID":26}},{"geometry":{"x":-1.3041197860999722E7,"y":3856327.957251977,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Assessing the neural dynamics of reading in deaf adults","Organization":"San Diego State University Foundation","City":"San Diego","State":"CA","Abstract":"Reading presents a significant challenge for individuals who are born severely-to-profoundly deaf because they cannot hear the language that is encoded by print. The factors that lead to skilled reading for deaf individuals are currently under debate and not well understood. For hearing individuals, phonological coding and awareness skills appear to be critical for reading success, but these skills are not good predictors of reading proficiency for deaf people. Furthermore, almost nothing is known about the underlying neural processes involved in the transition from identifying visual letter features to accessing word meaning for deaf readers. This project is designed to investigate the brain response to reading in deaf adults and the factors that predict variation in those responses. By identifying factors that do (and do not) affect reading processes, this project will inform educational models of literacy instruction and reading remediation for deaf people. In addition, deafness has a substantial impact on the ability of students to gain access to research careers because of communication roadblocks that hamper interaction with hearing scientists. The principal investigators have deaf-friendly labs (e.g., project staff are fluent in ASL) and provide training that facilitates the entrance of deaf students into scientific and academic fields. Thus, a parallel aim of the project is to increase the representation of deaf people in science by including deaf researchers on the project and by providing an accessible environment for deaf students to gain training and research experience.<br /><br />With support from the National Science Foundation, Dr. Karen Emmorey, Dr. Philip Holcomb, and their colleagues will use behavioral and neurophysiological measures to identify what factors predict variations in the brain's response when deaf adults read and recognize written words (e.g., spelling ability, phonological awareness, signing ability, reading speed). Cutting edge source localization techniques will be used to constrain and identify the neural location of the brain's response as measured by electroencephalography (EEG). The project is designed to illuminate the neural dynamics of reading for deaf people who are bilingual in English and American Sign Language and to understand how the neural components of reading are shaped by deafness, i.e., by the changes in visual attention and phonological abilities that result from congenital hearing loss. These discoveries will have theoretical import for understanding the neural plasticity (and invariance) of the reading system, as well as practical implications for developing reading interventions for deaf individuals.","FID":27}},{"geometry":{"x":-1.305128071646007E7,"y":3883606.4358160696,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"EAGER: Enabling Discovery and Scientific Collaboration on Human Memory via the Web-Based Atlas and Tissue Bank for Patient H.M.'s Brain","Organization":"University of California-San Diego","City":"La Jolla","State":"CA","Abstract":"Knowledge of a specific neural network supporting memory function in the human brain stems from the case of patient H.M. who, in 1953 underwent an experimental medial temporal lobectomy in the hope of reducing the frequency and severity of his epileptic seizures. The operation was successful in that respect, but it unexpectedly left him incapable of creating new memories. For more than five decades, H.M. participated in hundreds of experiments and his case was discussed in thousands of scientific publications. His brain contained the clues to understand how memory works; however, determining with precision which structures were damaged was not possible because even the latest neuroimaging could not clearly resolve the anatomy of the temporal lobes. With support from the National Science Foundation, Dr. Jacopo Annese will complete an 'open source', web-based microscopic atlas of H.M.'s brain which was donated to science post-mortem. The tools-embedded atlas will support the creation of teaching curricula that will expose students to raw neuroimaging data from multiple modalities, cutting edge brain mapping algorithms, web-based exploration tools, all within the clinical and biographical context of H.M. as an individual. The cyber infrastructure created through this project is expected to enable discovery neuroscience by participants world wide. <br /><br />Specifically, Dr. Annese and his research team will (1) provide a dedicated support infrastructure to maintain and manage the web atlas for H.M.'s brain; (2) significantly increase the accuracy of the atlas by increasing the number of digitized histological slices to achieve 1 mm per slice interval (from 3mm interval); (3) acquire and deliver image stacks to enable remote quantitative studies; (4) implement new web tools to enable the handling of remote request and curation of results from different laboratories; (5) convert the images into formats that can be 3-D printed using consumer products. Such cyber infrastructure will make the valuable H.M. data available for new retrospective studies that may further change our current view of how memory is established in the human brain and enable quantitative analyses at the cellular level using a 'virtual microscope'. The resulting atlas will be used by researchers worldwide to re-interpret, based on clear anatomical evidence, the results from hundreds of neuropsychological exams conducted when H.M. was alive.","FID":28}},{"geometry":{"x":61063.21362861743,"y":6895093.16128594,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: New Tools for Real-Time Imaging of Molecular-Resolution Connectomics of Synapses","Organization":"Old Dominion University Research Foundation","City":"Norfolk","State":"VA","Abstract":"PI: Xu, X. Nancy<br />Proposal: 1450936<br />Title: BRAIN EAGER: New Tools for Real-Time Imaging of Molecular-Resolution Connectomics of Synapses<br /><br />Significance<br />The successful outcome of this EAGER project will have a broad impact in neuroscience. The proposed project will offer new insights into the roles and functions of neurotransmitters in synaptic plasticity and regeneration. This will lead to the development of innovative tools for molecular identification and characterization of roles and functions of multiple types of neurotransmitters, their receptors, and their interactions and dynamics in synapses at the spatial and temporal resolution level. These powerful new tools are expected to become extremely valuable in addressing a wide range of pressing biological, biochemical and biomedical questions related to molecular and real-time characterization of functions of single live cells (neurons). <br /><br />Technical Description<br />The brain comprises large number of neurons, which are not continuous. Synapses enable them to communicate complex and specific commands with each other by passing specific electrical or chemical signals to another cell. Each synapse contains extensive arrays of molecular machinery that links the membranes of the coupled partner neurons, an array of neurotransmitters and their receptors. The aims of this project is to develop a novel imaging platform, including next-generation multicolored far-field photostable optical nanoscopy (PHOTON) with photostable multicolored single molecule nanoparticle optical biosensors (SMNOBS). This platform will quantitatively image and molecularly characterize roles and functions of multiple types of molecules (neurotransmitters, receptors) at individual live synapses in real time at nanometer (nm) resolution. These capabilities will enable the identification of the roles and functions of single neurotransmitter-receptor interactions, identify and characterize their roles in modulating and regulating functions of single synapses and neurons in real time. They will use the multicolored PHOTON: (i) to quantitatively and simultaneously detect and map diffusion and molecular dynamics of multiple types of neurotransmitters, their receptors and their interactions on each synapse with both spatial and temporal resolutions; (ii) to construct the connection of individual neurons at individual synapses at the molecular resolution; (iii) to explore the possibility of creating connectomics to determine the functions and related molecular pathways of synapses and their roles in neuron and brain functions at the molecular resolution level.","FID":29}},{"geometry":{"x":-1.2459275118278872E7,"y":4963387.1116635995,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Electrogenetic Reporters of Neural Activity","Organization":"University of Utah","City":"Salt Lake City","State":"UT","Abstract":"Genetically-encoded reporters of neural activity are a transformative tool for understanding brain function because they allow for the simultaneous measurement of activity across many neurons defined by genetic and anatomical criteria. The current generation of such reporters use light to signal activity, which limits their ability to be used deep in brain tissue and across the full range of neuronal activity. The goals of the project are to overcome these limitations by developing reporter proteins that can be engineered to emit unique electrical or magnetic signals in response to neural activity. The project will also develop sensors that are optimized for detecting these signals from individual neurons in intact brain tissue in the freely-behaving animal. The proposed 'electrogenetic' toolbox will allow neural activity to be recorded with high fidelity from defined cell types across the entire physiological range of neuronal firing rates, from any location in the mammalian brain, and in the freely-behaving animal. This strategy leverages existing and widely available technology for recording electromagnetic signals in the brain, and thus has the potential to be rapidly adopted for a wide range of neuroscience applications. <br /><br />This project will develop a new strategy for measuring neural activity from genetically-targeted neurons in the intact brain. An interdisciplinary team of investigators will first use gene therapy techniques to express candidate proteins in particular neurons, then will screen for electrical or magnetic signals using conventional electrodes or nanoscale magnetometer probes. Understanding how neurons of a particular type are activated in the behaving animal is crucial for understanding the neural basis of sensation, cognition and behavior. Indeed, the lack of tools for interrogating identified neurons while they are in action is a major impediment to understanding functional neural circuits in the brain. In addition to breaking this impasse in basic science, a potential broader impact of this project is that the tools to be developed in this proposal may provide information leading to improved diagnosis and treatment of nervous system disorders including mental illness, autism, addiction and epilepsy.","FID":30}},{"geometry":{"x":-8174895.596341525,"y":4994509.30521948,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Three Dimensional Optical Control of Neuronal Circuits during Behavior","Organization":"Cold Spring Harbor Laboratory","City":"Cold Spring Harbor","State":"NY","Abstract":"A central goal of systems neuroscience is to describe behaviors in terms of the neuronal circuits that control them. This constitutes a monumental challenge in the mammalian brain because behaviors are thought to rely on widely distributed neural representations, which are technically difficult to monitor at large scales or to manipulate at cellular resolution. This research will implement, optimize, and ultimately broadly distribute via online repositories and workshops, a three-dimensional, two-photon microscope, exploiting patterned illumination strategies for fast manipulation and monitoring of large neuronal populations in behaving animals. First, the PI will implement and optimize a dual photo-stimulation system to enable both precise two-dimensional illumination across wide fields of view using a digital micro-mirror device, as well as high-resolution three-dimensional stimulation using digital holography. Photo-stimulation will be combined with two photon resonant scanning imaging to achieve fast sampling rate of hundreds of neurons across large brain volumes. Second, these technologies will be demonstrated for in vivo use, in head-fixed behaving rodents, optimizing their applicability for experimental use. This approach will enable dynamic testing of the functional roles of arbitrary neurons and combinations of choice in behaving rodents. <br /><br />This project will develop and implement innovative optical methods for fine patterned stimulation of nervous systems and other excitable biological tissues. The approach will exploit current light-sensitive ion channels that can be inserted into neurons using the techniques of optogenetics. The planed optical illumination methods will, for the first time, allow fine spatial control and monitoring of brain activity. Further, these developments will provide new applications for high-resolution three-dimensional optical control of intra- and inter-cellullar signaling processes in any optically accessible tissue, greatly broaden their applicability in biological research and bioengineering. The project will result in broad distribution among interested scientists of all the methods developed. In addition, the results will be used to increase the awareness among the general public of the relevance of applied optics to daily life. These goals will be achieved through a concerted outreach program including optical imaging courses in Cold Spring Harbor Laboratory, volunteering internships, and lectures to local schools in Long Island and New York City.","FID":31}},{"geometry":{"x":-1.3609985767632734E7,"y":4561863.294001021,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Analysis of brain circuits with optically controlled synaptic GPCRs","Organization":"University of California-Berkeley","City":"Berkeley","State":"CA","Abstract":"The connectivity of brain circuits is central to how sensory information is processed, motor activity coordinated, memories stored and retrieved, and how behaviors emerge. While new physical connections can form and old ones be eliminated, much of brain processing depends on how synaptic inputs are integrated and how their strengths are dynamically adjusted. To understand neural connectivity one must develop the means to directly manipulate synaptic transmission by controlling the neurotransmitter-gated receptors of synapses. We propose to do this by engineering optical control into neurotransmitter-gated G-protein coupled receptors (GPCRs). These light-controlled receptors can answer questions at every scale of analysis of the nervous system, from elucidating the contribution of a specific subtype of a neurotransmitter receptor to transmission and plasticity, to the events in a single dendritic spine, to understanding the role of pre- and postsynaptic receptors in neural computations, to understanding the synaptic basis of circuit operations and the role of those circuits in behavior and sensation. An additional and critical part of the project is tool dissemination and web-based tutorials, which will be a high priority for the researchers. Training will be provided to the broader scientific community during the annual Berkeley Advanced Imaging and Microscopy workshop. The proposal involves an international collaboration in research and training with Israel, which will expose students from the US and Israel to the expertise of the labs in the collaborating countries.<br /><br />GPCRs form the largest class of membrane signaling proteins. They respond to a wide-array of stimuli. The roles of many GPCRs in neural circuits and behavior are not well-understood. Part of the problem is that the same GPCR may be found on presynaptic excitatory and inhibitory nerve terminals, postsynaptic dendritic spines and on associated glial processes. Another is that even though multiple GPCRs in a cell may couple to the same G-protein they often activate distinct targets due to molecular interactions that localize them to specific protein complexes. Thus, to determine the function of a GPCR one needs tools for that are subtype and cell-type specific, that are spatially precise, and that are rapid and reversible. In this project, individual full-length GPCRs that can be activated or blocked by light will be developed. Specifically, light-gated versions of the group I metabotropic glutamate receptors (mGluRs) will be engineered and then used to study synaptic plasticity.","FID":32}},{"geometry":{"x":-8518187.131846664,"y":5224750.499998765,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Collaborative Research: BRAIN EAGER: Stretchable graphene transistors for high signal, high channel count neural recording","Organization":"Cornell University","City":"Ithaca","State":"NY","Abstract":"This award is jointly made by two programs the Instrument Development for Biological Research program (IDBR) and Emerging Frontiers (EF) in the Directorate of Biological Sciences (BIO).<br /><br />A key roadblock to expanding our knowledge of the brain is that existing tools to probe its function are simply not up to the enormity of the task. Techniques for recording neural signals allow at most signals from tens or hundreds of neurons to be recorded, when thousands or even millions are needed. To address this challenge, improved types of sensors are required that record neural activity with greater signal quality and are more suited to parallel recording than current approaches. This collaborative project will develop a new type of sensor based on flexible graphene transistors. Graphene is an atomically thin sheet of carbon atoms that exhibits desirable physical, chemical, and electrical properties for interfacing with biological systems. However, the use of graphene transistors for single neuron sensing is largely unexplored. Open questions include the nature of the contact between the neuron and the graphene, the ultimate strength of electrical signals, and the long-term biocompatibility of graphene-based electrodes in the brain. Our proposed work will address these fundamental questions. If successful, this project will ultimately lead to societal benefits such as better neural prosthetics and new treatments for neurological disorders. Training opportunities at the interface of nano- and neuroscience, a key area of need for America?s technological future, will be available for graduate students.<br /><br /> 100% without degrading their electrical properties. The current project will investigate the electrical and mechanical interactions between kirigami graphene and individual neurons. Graphene will be cut into different patterns to optimize the mechanical contact between graphene and single neurons. Wrapping of graphene on the neuron will be maximized and the graphene will be used to measure voltage spikes produced by individual neurons, both in vitro and in vivo. With optimized conformal contact between graphene and neurons it will be possible to measure a large fraction of the intracellular potential (~ 70 mV). The semiconducting properties of graphene will also be used to amplify the bioelectronic signals to robust levels to facilitate multiplexed detection of thousands of neuron signals.","FID":33}},{"geometry":{"x":-8781794.120115379,"y":4297087.162275121,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Genetically Encoded Light Sources for Non-Invasive Optogenetics","Organization":"Duke University","City":"Durham","State":"NC","Abstract":"PI: Hochgeschwender, Ute H.<br />Proposal: 1450216<br />Title: BRAIN EAGER: Genetically Encoded Light Sources for Non-Invasive Optogenetics<br /><br />Significance<br />The realization of light-driven genetically targeted neuronal activation and silencing has led to unprecedented possibilities in manipulating neuronal activity in the behaving experimental animal.<br />However, translation of this approach into the clinical arena for potential therapeutic applications is complicated by the need for implanting optical fibers in the brain as the light source for activating lightsensing opsins. This proposal describes an integrated research, education, and outreach program which focuses on developing a new generation of genetically encoded light sources for non-invasive manipulation of optogenetic sensors. If successful this will be a key threshold advance that will provide the foundation for new technologies enabling minimally invasive and highly efficient diagnostics and therapies. Currently there are no alternative approaches which would achieve, non-invasively, the full range of photonic control of neurons as proposed here.<br /><br />Technical Description<br />The investigators will build on the highly innovative concept of combining optogenetics with bioluminescence. To exploit the concept?s potential for non-invasive light activation of optogenetic sensors in clinical settings, they will utilize protein engineering to both improve light output and extend the emission spectrum of the luciferase by optimizing intramolecular bioluminescence resonance energy transfer (BRET) between Gaussia luciferase and various fluorescent proteins. They will test the novel constructs for their efficiency in activating channelrhodopsins and proton and chloride pumps in vitro. The development of these concepts and reagents will have potentially transformative and broad impacts on the implementations of optogenetics in medicine.","FID":34}},{"geometry":{"x":-8561865.684953116,"y":4717075.855840491,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Wireless Measurement of Neuronal Currents Using Spin-Torque Nano-Oscillators","Organization":"University of Maryland College Park","City":"College Park","State":"MD","Abstract":"This award is jointly made by two programs the Instrument Development for Biological Research program (IDBR) and Emerging Frontiers (EF) in the Directorate of Biological Sciences (BIO).<br /><br />The brain is a complex network of interconnected circuits that exchange signals in the form of action potentials. These action potentials hold the key to understanding cognition and complex thought. Currently available non-invasive methods for probing neuronal activity cannot achieve sufficient spatial or temporal resolution to observe individual action potentials from single neurons or small clusters, which is a major limitation. This principal investigator proposes to study a novel approach for non-invasive measurements that will be able to read out individual action potentials across the entire brain. This project will take advantage of recent advances in spintronic devices to create injectable nano-reporters that will detect weak electrical signals in the brain and convert them to microwave signals that can be detected wirelessly outside the body. The detection device to be used is the spin-torque nano-oscillator (STNO), which converts electrical signals into microwave field oscillations that can be detected wirelessly. This approach could ultimately lead to the first non-invasive technology capable of measuring activations of individual neurons and small-scale neuronal networks in live primates and humans. This capability would have a major impact on our understanding of the inner workings of the brain and cognition. It could also have important clinical applications, particularly in the areas of neurological disorders and brain machine interfaces. <br /><br />The ability to monitor neuronal activity at the cellular level non-invasively is crucial for attaining a better understanding of cognition, as well as many clinical applications. Currently, all non-invasive methods for monitoring brain activity cannot simultaneously achieve the spatial and temporal resolution required to sense individual action potentials from a single neuron. This project is a novel approach for non-invasive measurements that will be able to read out individual action potentials across the whole brain from single neurons. To achieve the transduction of electrical activity to microwaves, a nano-sized device called a spin-torque nano-oscillator (STNO) will be used that converts steady electrical signals into microwave frequency magnetic field oscillations that can be detected wirelessly. The STNO responds in microseconds to electric signals, and thus can be directly used to measure individual neuronal action potentials. In addition, the STNO is a nano-scale device and can report on the firing and location of a single neuron. This project represents the first application to neurobiology of the exciting and rapidly evolving field of spintronics. A test system will be developed that includes a neuron simulator (a tunable circuit that simulates the voltages and impedance of a single neuron) and a high sensitivity microwave receiver to demonstrate the ability of these devices to report that activation state of a neuron wirelessly. this project also involves the design, fabrication, and test optimization of STNO devices for neurobiological applications. The ultimate and specific goal of this EAGER project is to perform a proof-of-concept demonstration of the proposed apparatus on a live squid axon.","FID":35}},{"geometry":{"x":-1.2353097063105864E7,"y":3792428.1373847383,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Integrated Measurement of Dopamine Release and Large-Scale Ensemble Activity in Behaving Animals","Organization":"University of Arizona","City":"Tucson","State":"AZ","Abstract":"This award is jointly made by two programs: the Instrument Development for Biological Research program (IDBR) and Emerging Frontiers (EF) in the Directorate of Biological Sciences (BIO).<br /><br />The neurotransmitter dopamine plays a central role in learning, decision making, motivation, and the control of movement. It is assumed that dopamine influences these functions by modulating the capacity of individual neurons to form brief or lasting connections with other neurons. This assumption, however, has not been tested as no instrument exists for the real-time measurement of both dopamine release and the activities of groups of individual neurons in freely-moving animals. To build such a device the following will be combined: fast-scan cyclic voltammetry, the current state-of-the-art technology for measuring dopamine release, and high-density extracellular electrode arrays for the real-time measurement of large groups of individual neurons. The instrument will be designed for recording in freely-behaving animals, giving scientists the unprecedented opportunity to address questions such as: Is communication between neurons in distant brain regions enhanced by dopamine release? Does such enhanced communication correspond with improvements in learning, decision making, or motor control? Does dopamine release during sleep coordinate the reactivation of neurons involved in a recent learning experience? Is such reactivation important for the formation of long-term memories? The societal impact of addressing questions such as these would be in the fundamental advances answers would bring to the understanding of the brain as an integrated system, how this system works during learning and decision making, and what goes wrong when components of this system break down due to neurological disease or injury.<br /><br />No tool exists that enables researchers to investigate the link between the activities of large groups of individual neurons and dopamine release in freely-behaving animals. The goal of this project is to build an instrument capable of measuring dopamine release and the activity of 100s of simultaneously active neurons in awake and behaving animals. The instrument integrates state-of-the-art technologies for measuring dopamine (fast-scan cyclic voltammetry) and neural activity (high-density ensemble recording). These technologies have not been integrated due to technical limitations. For example, electrical pulses created during voltammetry interfere with neural recording. Our methods are 1) adapt a recently-developed multi-channel headstage amplifier into our recording system that rapidly adapts to electrical artifacts, and 2) develop a novel carbon-film coating for metal electrodes, permitting dopamine recordings from electrode arrays. Our approach is to identify technical hurdles by troubleshooting and collecting scientific data from the system in anesthetized and freely-behaving rats. The two-year scope of this study is to collect and publish scientific and technical data from fully functional prototypes. These data will support funding efforts to build and distribute a commercial product. The theoretical foundation inspiring this work is that dopamine modulates decision making, learning, and motor control through its ongoing regulation of plasticity and neural activity in neuronal groups. According to the reinforcement-learning theory of dopamine function, dopamine release following unexpected rewards triggers associative learning and plasticity in networks of neurons. The question of how activity and connectivity are regulated by dopamine in behaving animals is unanswered and the proposed instrument will help fill this gap in understanding.","FID":36}},{"geometry":{"x":-1.3050860312804502E7,"y":3884944.083811064,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Socially Situated Neuroscience: Creating a suite of tools for studying sociality and interoception","Organization":"University of California-San Diego","City":"La Jolla","State":"CA","Abstract":"The social world exerts a powerful influence on our behavior and our brains. Yet, much of our knowledge regarding the function of neurons in the brain is based on neural recordings from animals or humans who are isolated from their social counterparts. Thus, there exists a knowledge gap that is largely due to the lack of recording and behavioral tools for doing experiments in the social realm that still allow proper experimental control. Dr. Andrea Chiba and colleagues aim to fill this gap by developing the following: 1) light, wireless, flexible recording sensors that can provide brain and body signals in a non-intrusive manner; 2) a robot with a synthetic, biologically inspired brain that can act as a socially relevant entity; and 3) a set of novel experiments to interrogate the function of brain circuits and their relationship to other biological signals during social interactions and decisions. The ability to record and integrate signals from the brain and body during complex social decisions will provide a research platform for studying and reconstructing brain signals to understand how the brain represents the social world. The new technology can eventually be scaled for use with humans, providing a means to better understand the neural basis of goal-directed social actions beyond what is currently feasible.<br /><br />In addition to its potential for advancing the understudied field of social neuroscience, the development of the tools will provide a cutting-edge platform to train the next generation of diverse interdisciplinary scientists. The research team is committed to public outreach and plans are in place for: 1) public talks, including to K-12 and undergraduate audiences; 2) dissemination of information through appropriate media outlets; and 3) launching a virtual robot competition to engage promising young scholars of diverse backgrounds in scientific careers, by highlighting exciting interdisciplinary research that links the study of brain and behavior with engineering approaches. <br /><br />Specifically, 3 major technologies will be developed and conjoined to comprise a suite of neuroscientific tools that include: 1) Flexible, stretchable, wireless sensors for detecting autonomic responses such as respiration rate and heart rate, both of which are modulated by social encounters; 2) integration of the autonomic signals with high-density neurophysiological wireless recording systems, as no such system exists currently. Approximations of these systems result in heavy instrumentation that disrupts ordinary movement and social behavior, so the second generation of this technology would include integration with injectable cellular scale opto-electronic devices; and 3) A synthetic life form (robot) to be further developed as a neuroscience research tool and a test bed for integration of theoretical principles gained from experimental data of the complex dynamics of neural systems. Ultimately, the neurally inspired architecture of the robot will, in turn, be expanded to include and synthesize the formal theoretical properties of neural systems essential to social function. The basic neuroscientific questions that can be addressed with these tools are boundless.","FID":37}},{"geometry":{"x":-8141898.350609416,"y":4999492.815428535,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: A Chemical Strategy for Identifying Functional Neural Circuits","Organization":"SUNY at Stony Brook","City":"Stony Brook","State":"NY","Abstract":"With this award, Scott T. Laughlin from Stony Brook University, funded by the Chemistry of Life Processes Program in the Chemistry Division of the National Science Foundation, will investigate the use of synthetic molecules for mapping the connections between neurons in the brain. The human brain's ~90 billion neurons allow us to think, move, and respond to stimuli. The brain's amazing properties stem from neural circuits, which perform logical operations based on the timing of neural activity and the specific connections between neurons in a circuit. Strategies for visualizing and controlling neural activity abound, but there are very few methods that enable direct imaging of neural circuit connectivity, and those that exist are imperfect. Bridging the fields of chemistry and neuroscience enables a novel strategy that will facilitate the direct visualization of neural circuit connectivity in order to better understand the brain. Importantly, this work will expose graduate and undergraduate students to cutting-edge methods and ideas in chemistry and neuroscience. <br /><br />The goal of this research is to create small molecules that illuminate the neurons that are connected to each other in a neural circuit. Currently, there are no known small molecules that display this property. However, there are a variety of naturally-occurring entities that mark neural circuits by moving through neural synapses, which are the functional connections between neurons. For example, some proteins called lectins can cross the synapse by virtue of their affinity for synapse cell surface sugars, but they are large, toxic, not easily altered, and slow to label consecutive neurons in a circuit. Interestingly, diverse lectins, from different organisms and with different sugar affinities share the ability to cross the synapse, suggesting that the most important property that endows lectins with the ability to cross the synapse is their general sugar affinity, and not a particular protein feature or specific sugar affinity. This research explores the idea that small molecules that mirror the trans-synaptic lectin's affinity for sugars will be able to cross the synapse and serve as tracers for mapping the brain's neural circuitry. The use of these trans-synaptic small molecules has the potential to enable an improved and detailed understanding of the brain.","FID":38}},{"geometry":{"x":-1.0964369735903872E7,"y":3429797.418901822,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Analyzing and modeling power-law behaviors in neuroscience","Organization":"University of Texas at San Antonio","City":"San Antonio","State":"TX","Abstract":"The objective of this EAGER project is to build and apply a computational toolbox to study and model power-law dynamics in the brain. Traditionally, any complex behavior in neuroscience is broken into the interactions of multiple components, each working in its own characteristic temporal framework. However, there is an increasing number of examples, such as in brain activity recording by electroencephalography (EEG), firing rate adaptation, and synaptic weight dynamics, in which the characteristic process follows power-law dynamics, which indicate that the time constant of a mechanism at one scale is highly correlated to the activity of the system at multiple scales. Therefore, the overall behavior of the system cannot be separated into largely independent components and traditional analysis techniques cannot provide an appropriate description of how the system works. In order to understand neuronal information processing at multiple scales it is necessary to develop a framework to analyze and model power-law dynamics at all levels of biological organization. This project plans to make widely available a unified platform to detect, analyze, validate, and model power-law behavior in the nervous system at multiple scales of organization. To broaden impact the team will generate products for the public that will explain the differences between power-law and exponential processes and their importance in neuroscience research. Research opportunities will be provided for students, especially underrepresented group at the University of Texas at San Antonio (UTSA), a minority serving institution. <br /><br />The collaborative team will analyze and model power-law relationships in large-scale brain activity and complex behavior. The project aims to build and validate a toolbox to test and characterize power-laws in data streams and to model power-law dynamical systems. For this purpose state-of-the art algorithms will be used to characterize experimental data and fractional differential equations to model power-law dynamical systems. This modeling platform will allow the study of power-law processes from the sub-cellular to the behavior scales. The toolbox will be applied to two very different problems dealing with complex pattern generation (birdsong production) and human language comprehension. Both applications will require the analysis of Big Data streams and model non-linear sequence production or decision-making. Although initially the focus of research will be in these two projects the framework will be built to be applicable to a wide range of neuroscience projects that can impact the research done under the BRAIN initiative. Interactive examples will be implemented using Mathematica and Matlab platforms and the team will also update and write new Wikipedia pages on the topics of this grant. In all projects, graduate and undergraduate students will be involved in both the research and educational components, providing opportunities not only to do research but to enhance their communication skills.","FID":39}},{"geometry":{"x":-7914376.428852677,"y":5214763.854516937,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Cell-type-specific Optogenetics in Wild-type Animals","Organization":"Massachusetts Institute of Technology","City":"Cambridge","State":"MA","Abstract":"This project consists of engineering a system for producing selective expression of light-inducible molecules in targeted neuron population in non-genetically modified animals of any species. The result will be a set of reagents that will be made freely available to the scientific community through nonprofit repositories and service centers. This new set of tools will enable the study of neural circuitry with greater resolution, power, and throughput than is currently possible, allowing major advances to be made in understanding the organization of the complex neural systems underlying perception, cognition, and behavior. This increased understanding could also result in improved artificial intelligence and machine learning. Finally, the future direct application of the technology in human patients holds promise for potentially treating conditions such as Parkinson's disease and epilepsy, by allowing the selective activation or inactivation of distinct components of the compromised neural circuitry that is associated with these disorders.<br /><br />Over the last decade, sophisticated genetic tools have been developed that allow control and monitoring of neuron electrical activity using light alone. \"Optogenetics\", as this area of technology has become known, is only useful if optogenetic molecules can be specifically expressed in functionally meaningful groups of neurons instead of broadly in all the diverse neuron types that are present in any brain region. This requirement has confined their use almost entirely to genetically modified (transgenic) mice and rats. The approach of using transgenic animals has three major disadvantages. First, the production and maintenance of transgenic rodents is very expensive. Second, even within transgenic rodents, it allows the optogenetic study and manipulation of only one or two cell types at a time, preventing powerful combinatorial experiments in which different neuron types are independently controlled within the same tissue. These combinatorial experiments will be critical for deciphering the complex interactions between cell types. Third, it restricts the experiments to rodents, preventing studies in other important taxa including primates, in which optogenetic experimentation during complex cognitive tasks would almost certainly provide major insights into the neural circuitry underlying cognition. This project aims to create engineered binding proteins that recognize selected endogenous proteins that will then act as scaffolds for assembly of transcription factors that will activate gene expression in specific neurons.","FID":40}},{"geometry":{"x":-1.0381439985776028E7,"y":5616615.678292976,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: A Massively Parallel Electrocorticographic Recording, Stimulating and Chemical Detection Device to Understand Neural-Network Functioning in Behaving Animals","Organization":"University of Minnesota-Twin Cities","City":"Minneapolis","State":"MN","Abstract":"This award is being made jointly by the Neural Systems Cluster in the Division of Integrative and Organismal Systems and the Instrument Development for Biological Research program (IDBR) in the Division of Biological Infrastructure. <br /><br /><br />How an animal renders a correct decision to select an appropriate behavior to express over another is not well understood at the level of individual brain neurons. Such decision making, however, is not always easy to study or understand because a number of factors can bias behavioral choice in dynamic ways (for example, fluctuating neurohormones or environmental conditions). Even in simpler invertebrate animals, with a reduced number of brain neurons, the operational state of their neural networks is neither easy to follow nor predictable. Thus to solve some of the most pressing questions in the field of neuroscience, technological advances must be made so that the functioning of brains can be studied under more naturalistic conditions. To this end, a team of scientists in engineering, nanoscience, chemistry, computer science, and biology will work together to design, fabricate and test a novel brain recording and stimulation device that, in parallel, will detect fluctuations in neuroactive substances. The team will begin by making prototypes of the device and testing it on leech and insect brains that have fewer neurons, but have well defined correlations between nerve cell activity and behaviors. The team is committed to the interdisciplinary cross-training of graduate and undergraduate students, especially females and underrepresented minorities. The goal of team mentoring is such that students will be well versed in both the biological and engineering aspects of the device. School visits are also planned to engage K-12 students in neuroscience, chemistry and engineering-related demonstrations, encouraging them to participate in STEM fields.<br /><br />The cross-disciplinary team will fabricate and test a novel multi-electrode integrated ElectroCorticoGraphy (ECoG) device and chemical sensing system having high temporal resolution. Patterned brain activity will be collected in parallel with neuromodulatory substances such as dopamine (DA), serotonin (5-HT) and octopamine (OA). The team?s aim is to fabricate a device that will be 2 x 2 mm square, micron-level thin, flexible and biocompatible for extended use, with a minimum of output wires; our future goal will be to develop a completely remote sensing/monitoring capability. Such post-fabrication modification will be conducted at the University of Minnesota?s Nano Center. Furthermore, the team aims to identify conserved neural algorithms or rules for context-dependent decision making that span the invertebrates (leech and honey bee) to non-human primates. Fabricated devices will be placed: 1) around dorsal and ventral aspects of the brain of the leech while it makes a decision to crawl or swim (DA and 5-HT-dependent switching); 2) over the Kenyon cells of the honey bee brain during a modified PER (proboscis-extension) learning-and-memory task (potential DA, 5-HT, and OA involvement); and 3) over the Prefrontal Cortex of monkeys during a spatial-cognitive task that will mimic one used for the honey bee (measuring DA changes).","FID":41}},{"geometry":{"x":-9660100.112518376,"y":4323740.541901245,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Graphene-based Microfluidic Platforms for Measuring Cell-Cell Communication in the Central Nervous System with Sub-Synaptic Resolution","Organization":"Vanderbilt University","City":"Nashville","State":"TN","Abstract":"Our brains are composed of trillions of dendritic spines and synapses that serve as sites of communication between neurons within complex neuronal circuits. Dendritic spines and synapses are thought be unique and display different properties and activities, which points to an urgent need to study individual spines and synapses within brain circuits. However, this is currently not feasible due to the lack of available technologies for investigating individual spines and synapses. In this project, a new technology will be developed that will allow researchers to examine the properties and activities of individual spines and synapses. Because a major function of spines and synapses is to transmit signals that control information flow within the brain, studying these structures at an individual synapse level will lead to a new understanding of how information is relayed among brain circuits to control cognitive function. Furthermore, since changes in the structure and function of spines and synapses are associated with many neurological disorders, insight gained from studies examining individual spines and synapses could lead to better treatments for various neurological disorders. Our project will combine the expertise of neurobiologists and engineers to develop the new technology. As such, training opportunities will be provided for both graduate and undergraduate students in an interdisciplinary environment that will be extremely beneficial to their long-term career development.<br /><br />To develop this technology, a new class of microfluidic platforms, with integrated graphene probes will be designed to investigate synaptic activity with single synapse resolution. Graphene-based sensors, which have the capability of detecting single molecular charge and capturing electrical and optical events in tens of picoseconds, will be combined with scanning photocurrent microscopy to detect local electrical and chemical signals at sub-synaptic resolution (~ 500 nm). These unique properties of graphene enable the new platform to map the activity of neurons with single synapse spatial resolution, sub-millisecond temporal resolution, and single-molecule-charge sensitivity. The obtained data with assays enabled by this new platform will provide new insight into the molecular mechanisms that underlie cognitive brain function.This award is jointly made by two programs the Instrument Development for Biological Research program (IDBR) and Emerging Frontiers (EF) in the Directorate of Biological Sciences (BIO).","FID":42}},{"geometry":{"x":-9821386.517906943,"y":4876436.912361155,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Multiscale dynamics and emergent properties of suprachiasmatic circuits in real time","Organization":"University of Illinois at Urbana-Champaign","City":"Champaign","State":"IL","Abstract":"This award is being made jointly by the Neural Systems Cluster in the Division of Integrative and Organismal Systems and the Instrument Development for Biological Research program (IDBR) in the Division of Biological Infrastructure. <br /><br />Understanding how the brain enables us to think, act, learn, and remember is challenging. Progress has been impeded by lack of a dynamic picture of interactions and properties that emerge when tiers of interconnected brain cells (neurons) are activated in response to experiences. These interactions cause changes in our behaviors and can affect subsequent activities of these neurons, a process called plasticity. This proposal will develop and use newly created, complementary technologies that will non-invasively control, measure, and analyze brain network dynamics and change in real time. Neuroscientists, engineers, and chemists from the University of Illinois at Urbana-Champaign will work together, each bringing cutting-edge methods to bear on this problem. Approaches include: 1) analyzing slices of brain tissue that maintain dynamic properties in a dish; 2) real-time, label-free imaging of neuron activity by novel optical methods; 3) activating and measuring neuronal activity with flexible, clear electrodes that interface directly with cells; and, 4) measuring and identifying patterns of brain chemicals released by experiences. These approaches will be applied together to better understand the dynamic geography of brain information processing and plasticity. Such comprehensive studies of brain dynamics in space and time have never been done. In the future, these technologies can be applied to many brain regions to advance understanding, broadening their impact. Students will be trained beyond usual disciplines, so that neuroscience, imaging technology, engineering of new materials for electrodes, and high-resolution analysis of neuron-to-neuron signals will be taught and used together. Outcomes will contribute to a workforce trained in new ways to tackle problems beyond current boundaries.<br /><br />What dynamic interactions and emergent properties of neuronal cells and circuits encode experience and generate changes in complex behaviors? Understanding the temporal and spatial dynamics of signal flow and evolution in multi-tiered neuronal circuits has been elusive. The proposed study will address this gap through transformational research that bridges excellence in fundamental neuroscience with innovative technologies in non-invasive imaging, materials development, and neurochemical analysis. Focus will be on processing of a surrogate sensory signal in the suprachiasmatic nucleus (SCN), the brain's circadian pacemaker, that generates long-term behavioral change. This initiative will enable a pioneering program to develop and integrate novel non-invasive imaging of action potentials assessed by quantitative phase imaging of optical signals, stimulation/sensing by original, transparent, biocompatible electrodes, and chemical analyses of complex peptide-release signatures to understand the spatiotemporal dynamics of information flow in rat SCN circuits. These approaches will be applied together to better understand the dynamic geography of brain information processing and plasticity. Such comprehensive studies of brain dynamics in space and time have not been done previously. In the future, these technologies can be applied to many brain regions to advance understanding, broadening their impact. Students will be trained beyond usual disciplines, so that neuroscience, imaging technology, engineering of new materials for electrodes, and high-resolution analysis of neuron-to-neuron signals will be taught and used together. Outcomes will contribute to a workforce trained in new ways to work beyond current boundaries.","FID":43}},{"geometry":{"x":-8175201.344454666,"y":4991604.698144642,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER:The Virtual Neuroanatomist: Using Machine Intelligence to Study Intelligent Machines","Organization":"Cold Spring Harbor Laboratory","City":"Cold Spring Harbor","State":"NY","Abstract":"Cutting-edge light microscopy technology allows entire vertebrate brains to be digitized, resulting in data sets of unprecedented size and complexity. However there is a lack of adequate computational tools to visualize, manage, analyze, and disseminate these enormous data sets, and visual examination by expert human neuroanatomists remains the standard method to extract information from microscopic images. Software tools exist that can perform simple operations, but they are not able to adequately mimic the visual pattern recognition skills of an experienced neuroanatomist. This project aims to develop computational tools that mimic the analysis of an expert neuroanatomist, thus allowing for rich data analysis of whole-brain light microscopy data sets on a scale that has been previously intractable using human experts.<br /><br />Machine vision algorithms will be developed and integrated into an an open source software toolbox (with associated whole brain image data) that will be made widely accessible for further development and refinement. Pattern recognition methodology will be applied to combine information about brain location (e.g., \"where are we in the brain\") with information about correspondence of brain structures in different species (e.g., \"which areas of the brain of these species correspond\"). Incorporating comparative neuroanatomical knowledge into pattern-recognition methodology is radically different from the \"atlas morphing\" approach currently used, and has the potential to transform the study of whole-brain neuroanatomy. The tools will help fill a gap in knowledge and skills (as contemporary neuroanatomists are increasingly less frequently being trained to study whole-brain microscopic anatomy), and postdoc and PhD students will be trained in the project.","FID":44}},{"geometry":{"x":-8525963.544063509,"y":4765215.359832677,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Discovery and characterization of neural circuitry from behavior, connectivity patterns and activity patterns","Organization":"Johns Hopkins University","City":"Baltimore","State":"MD","Abstract":"Johns Hopkins University is awarded a grant for research leading to an improved understanding of how the brain is connected. Drosophila larvae, with 10000 neurons (and about 1000 neuron types), offer an opportunity to determine how an entire nervous system generates behavior. The research combines information from three sources: a neuron activity map of the entire Drosphila larval nervous system; a library of neuronal lines yielding a neuron behavior map; and a \"wiring diagram\" or connectome for the entire larval nervous system. Together, the neuron-behavior map, the neuron-activity map, and the connectome complement one another, laying the groundwork for a brain-wide understanding of the principles by which brains generate behavior.<br /><br />The technical goals for this project will be to develop principled statistical pattern recognition & machine learning methods for clustering neurons based on three different data sets, both individually and jointly. The extent to which clusters obtained from the three datasets agree, and the manner in which they disagree, will reveal how the structure of neural circuits relates to their function and how brains generate behavior. Current methods for discovery and characterization of neural circuitry from behavior, connectivity patterns and activity patterns - fusion and inference from multiple disparate data sources- are insufficient; the approach developed in this project will yield improved methods developed in conjunction with neuroscientists.","FID":45}},{"geometry":{"x":-8799183.39431728,"y":4291821.362968827,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Panoramic, dynamic, multi-region two-photon microscopy for systems neuroscience","Organization":"University of North Carolina at Chapel Hill","City":"Chapel Hill","State":"NC","Abstract":"This award is made by the Instrument Development for Biological Research program (IDBR)in the Division of Biological Infrastructure (DBI; BIO Directorate).<br /><br />The cerebral cortex, the outer layer of brain, has greatly expanded in surface are during mammalian evolution. This cortical region is parcellized into discrete functional areas including visual cortex, motor cortex, and language areas. These brain areas act in concert to support behavior. Although we have learned much about how to ascribe function to particular brain areas, we know little about the cellular mechanisms by which this concert is conducted. Model systems, including mice have discrete functional areas in their brains. However, the current tools that neuroscientists have for investigating activity in brains are limited to either a sparse sampling of neurons distributed over large areas, or a large density of neurons in a single area just 500-700 microns across. Thus, it is tremendously difficult to make progress in understanding how cortical areas act in concert to support behavior. The proposed research project will develop a new type of microscope which will be able to detect single neuron spiking across a field of view of several millimeters. This area can encompass five or more cortical areas in a mouse. In addition, this microscope will contain high speed spotlights for simultaneously imaging neuronal activity in multiple cortical areas. This time resolution is crucial for understanding the information neurons encode, their dynamics during behavior, and their connectivity. A community of scientists across the US and the globe will be cultivated to disseminate the research, aid in its implementation, and accelerate collaborative progress in neuroscience. Workshops will also be held to train scientists in advanced optics and neuroscience. Ultimately, this project will provide new technology that is crucial for the BRAIN Initiative, and will foster a broader scientific community for further progress in the field of two-photon imaging. <br /><br />The research team will develop a two photon (2p) imaging system with a wide field-of-view (FOV) (~ 3 mm) and cellular resolution across the full FOV. To ensure high temporal resolution of recorded activity, they will also develop multiplexed beams that image brain regions within the FOV at high speed. These multiplexed beams can be dynamically reconfigured to target different areas within the full FOV, like spotlights. The approach is to model the full system and create optimized optical subassemblies, including a custom objective. The team will make calculated engineering tradeoffs to preserve cellular resolution while still achieving a wide FOV. High speed scanning will be developed using resonant scanners and photon counting electronics. This system is scalable, as the beam multiplexing can be modularized, and multiple modules can be stacked to increase the number of beams, so long as the fluorescence lifetime is shorter than the interval between laser pulses. Thus, the Trepan2p (Twin-Region, Panoramic 2p), will enable direct measurements of cross-correlations and moment-to-moment, dynamics in extended brain networks. This technology will enable previously impossible experiments, imaging neuronal activity with single cell resolution across extended neuronal circuitry in an array of model systems including mice and primates.","FID":46}},{"geometry":{"x":-1.3050248816578217E7,"y":3883262.4691887856,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: A novel toolkit for imaging transcription in vivo","Organization":"University of California-San Diego","City":"La Jolla","State":"CA","Abstract":"Learning requires the conversion of transient experiences into long-lasting changes in neural circuitry. Animal behavior triggers changes in gene expression in small populations of neurons and behaviorally induced genes regulate synapses and neuronal morphology. Yet, it is unclear if changes in gene expression are the cause of behavioral plasticity, or the consequence. This project will develop a new genre of fluorescent reporters that enable the visualization and manipulation of endogenous transcription factors in individual neurons, in real time, and within the brain of behaving animals. During the award period, candidate reporters will be made that recognize six different transcription factors. These reporters will have widespread utility for investigating the molecular mechanisms that support learning in vivo and analysis of populations of neurons that are active during a learning paradigm. The development of these reporters includes ongoing training of undergraduate, graduate, and postgraduate scientists. Student training is optimized with guidance from the CREATE STEM Success Initiative on the UCSD campus. <br /><br />Inducible transcription factors (ITFs) translate signals that last milliseconds or seconds into changes in cellular function that may persist for hours, days, or longer. This project will develop genetically encoded transcription factor reporters (GETFaRs) that are designed to visualize or manipulate an ITF. GETFaRs are based on molecular scaffolds, engineered through a process of synthetic affinity maturation of camelid nanobodies (Nbs) which bind the endogenous ITF. The Nb protein will be fused to a fluorophore or DNA modifying enzyme, allowing users to visualize or manipulate endogenous transcription factors. A degradation signal (degron) will be incorporated into the Nb near the ITF binding site. Consequently, GETFaRs will be constitutively expressed and rapidly degraded in the cytoplasm. When the ITF is expressed, the GETFaR-ITF interaction will mask the degron, stabilizing the complex. The ITF's nuclear localization signal will translocate the complex into the nucleus, resulting in stabilized GETFaRs that accumulate in the nucleus and stoichiometrically reflect ITF expression. Candidate GETFaRs will be validated in vitro using standard biochemical and imaging techniques and in vivo using two photon imaging of neurons in head fixed mice. Optimal GETFaRs will enable research that 1) monitors or manipulates transcriptional states during learning, 2) studies the emergence of ensembles of co-active neurons within a circuit, 3) probes the dynamics of chromatin and nuclear organization, and 4) analyzes the genome of defined populations of neurons responding to complex, natural stimuli.","FID":47}},{"geometry":{"x":-8784698.727190217,"y":4299686.021236818,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Integrative Cross-Modal and Cross-Species Brain Models: Motivation and Reward","Organization":"Duke University","City":"Durham","State":"NC","Abstract":"Motivation translates goals into action, and significantly impacts cognition along several dimensions. The motivation for reward biases attention, perception, and memory, and enhances learning, with effects evidenced behaviorally as well as in specific brain regions. However, given such broad effects of reward motivation, the question remains: how does reward motivation propagate throughout the brain and how does it dynamically change the greater neural circuitry to prime us to behave appropriately? In order to answer these questions we develop statistical models for the effect of motivation on neural circuitry, which combine data recorded using different instruments across a variety of species. A fuller understanding of the neural effects of motivation would elucidate how it impacts important cognitive processes, yielding insights that are useful for better performance in various arenas, from education to therapy. <br /><br />In order to gain a more complete understanding of the neural network dynamics underlying the behavioral and cognitive effects of motivation, it is necessary to integrate research in human subjects, and in animal models. While extensive and crucial research has been carried out on reward motivation separately in humans and animal models, there is a clear need for improved translation across species. An overarching analytical framework for translation is extremely important, due to the complexity of the problems being addressed, and to leverage the strengths offered by each species and available technology. The aim of this work is the development of dynamic, hierarchical Bayesian models to discover functional neural networks that can translate across species and data collection modalities. Bayesian models of human behavior, and Bayesian machine learning inspired methods for neural network modeling, have been extremely successful, making Bayesian methods fertile ground for explorations into translational neural network discovery.","FID":48}},{"geometry":{"x":-9826278.487717194,"y":4879494.393492563,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Spatially-Resolved In Vivo Optogenetic Stimulation and Imaging Platform","Organization":"University of Illinois at Urbana-Champaign","City":"Champaign","State":"IL","Abstract":"PI: Boppart, Stephen A.<br />Proposal: 1450829<br />Title: BRAIN EAGER: Spatially-Resolved In Vivo Optogenetic Stimulation and Imaging Platform<br /><br />Significance<br />The successful outcome of this research project will have a broad impact in neuroscience in addition to optical science and engineering. The PI will use implanted imaging fiber bundles that will enable<br />in vivo imaging as well as spatially-controlled optical stimulation and optical feedback of <br />large-area neural circuits. Current fibers only indiscriminately illuminate large-areas. Optogenetics is expected to make a broad impact in neuroscience, as well as medical science and clinical medicine in the future. This proposed research offers the potential to have an even greater impact by controlling the light stimulus and enhancing specificity in the control of neural circuits. The results of this project will be shared widely amongst the scientific and engineering communities, and also across wide segments of society in outreach activities. The new imaging and visualization capabilities will inspire K-12 students to think about how technology can be used to see things one cannot normally see, and how we can invent new ways of seeing the world around us and discovering new knowledge. Outreach activities will include demos of these imaging fiber bundles and novel light sources to K-12 and community groups through<br />annual Engineering Open House events, as well as integration of these technological methods in Prof. Boppart?s undergraduate ECE/BioE 467 Biophotonics and ECE/BioE 380 Biomedical Imaging<br />courses.<br /><br />Technical Description<br />Optogenetics is a rapidly developing field with an ever-expanding toolkit of molecular biology<br />techniques to enable light-activated switching and control of cells, most commonly neurons.<br />Equally significant advances have occurred in optical science and engineering. By understanding<br />and exploiting physics-based principles of how light interacts in photonic crystal fibers (PCFs) and within imaging fiber bundles, it is possible to generate, control, and optimize a wide range of new optical parameters for in vivo optogenetic stimulation. Traditionally in in vivo optogenetic applications, light has been sent down single multi-mode optical fibers to diffusely illuminate the brain, relying on the molecular biology of optogenetically-modified neurons for cell and circuit specificity. This EAGER project will uniquely develop and demonstrate the use of imaging fiber bundles, and the generation of specific light pulse parameters to enable spatially-resolved optogenetic stimulation and imaging of neural circuits in vivo. These novel neurotechnologies will enable new investigations underlying behavior and cognition.","FID":49}},{"geometry":{"x":-7909885.3336757785,"y":5215813.256919098,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Robust longitudinal characterization of brain oscillations in the first 3 years of life","Organization":"Children's Hospital Corporation","City":"Boston","State":"MA","Abstract":"The human brain undergoes rapid and profound changes during the first 3 years of life, which accompany the emergence of new cognitive skills, including remembering and recognizing faces and objects, acquiring vocabularies, and focusing attention on the task at hand, among others. While such a rich repertoire of functions requires the coordination of multiple brain regions, little is known about how changes in the brain's electrical activity across different brain regions correlate with changes in behavior. This knowledge gap is in part due to methodological limitations imposed by the predominant brain imaging method, functional magnetic resonance imaging (fMRI). fMRI not only requires infants or toddlers to remain still or asleep during the observation, but also cannot directly measure rapid changes in neuronal activity at a high temporal resolutions (millisecond). With recent technological and computational advances, it has become possible to overcome these technical barriers and obtain direct measurements of brain electrical activity in behaving infants. With the support of the National Science foundation, Dr Stamoulis and colleagues at the Laboratory of Cognitive Neuroscience at Boston Children's Hospital/Harvard Medical School, will have the rare opportunity to systematically characterize development-related changes in neural signals derived from longitudinal hdEEG data acquired in infants and toddlers repeatedly across 3 to 36 months of age using a number of advanced computational approaches. This study will provide fundamental information regarding how the brain changes across early development. Findings from this project are also expected to help educate families on how early experiences shape the brain and facilitate cognitive functions, and will inspire the development of new courses and instructional materials to educate students, researchers and clinicians on the relationships between behavioral and neural mechanisms of cognitive development.<br /><br />The project is an ambitious attempt at characterizing changes in the developing human brain by analysing high-density electroencephalography (hdEEG) data collected from the same infants across the first three years of life using source localization and frequency analysis of neural oscillations within and between different functional brain regions. The investigation will focus on characterizing oscillatory waveforms of brain electrical signals originating from different spatial locations across multiple time points during early development. The power of these waveforms in different frequency bands, e.g. theta, alpha, beta, and gamma power, are known to emerge at different time points during early development and to be associated with variations in external stimuli, information processing demands, and behaviors. However, age-related changes in the dominant oscillation frequency, power and spatial distribution among brain regions have not been systematically characterized during this age range. Longitudinal high-density EEG data from about 200 typically developing infants at 3, 6, 9, 12, 18, 24, and 36 months of age will be analyzed under the same type of tasks and no-task conditions. Novel source analysis methods will be applied to hdEEGs, to extract and localize dominant sources and to decompose source signals into individual oscillation components and compare them across ages. Resting and functional networks and directional connectivities between identified sources will also be systematically quantified and compared across ages. This project is expected to provide a new source-based language for investigating human brain development using EEG and to reveal how neural signals change in time, frequency and brain spaces to enable infants to communicate with the world and to acquire new skills.","FID":50}},{"geometry":{"x":-8287046.558599449,"y":4938103.981012395,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: The Molecular Interactome of Synaptogenesis","Organization":"Rutgers University New Brunswick","City":"New Brunswick","State":"NJ","Abstract":"The primary objective of this EAGER project is to provide infrastructure that will have broad scientific and social impacts. The scientific information and reagents generated in this project will impact a wide range of scientific activities relevant to the NSF BRAIN Initiative. The protein interactions uncovered will provide the basis for hypothesis-driven research neurobiology programs in humans and model organisms. Discovery of the ensemble of molecular interactions of the synaptic cleft, and sharing these data and reagents with the scientific community, will provide stepping stones for many other projects, increasing the overall rate of discovery in neuroscience, developmental and structural biology, proteomics, and related fields. The PIs have a strong commitment to undergraduate teaching in their laboratories, and have extensive experience training undergraduate and minority students in research projects. Several aspects of the proposed BRAIN EAGER project, and the anticipated follow-up structural and functional studies of synaptic proteins, are ideally suited for such undergraduate projects. The interdisciplinary nature of our EAGER proposal, at the interface of neurobiology, cell biology, systems biology, bioengineering, bioinformatics, and molecular biophysics, will allow the PIs to expand their undergraduate research programs, and to proactively recruit undergraduate minority students into these programs, training the next generation of molecular neuroscientists.<br /><br />It is estimated that the human brain is composed of about 120 billion neurons, connected through more than 100 trillion synapses. Despite the astronomical number of possible connections, during development the brain is wired with exquisite precision so that brain circuits precisely integrate and process sensory inputs to generate proper motor outputs as well as behavior and social interactions. At the cellular and molecular level, each individual synapse requires the apposition of structurally and functionally matching pre- and post-synaptic protein pairs. Although there are trillions of synapses, each synapse is likely to be unique. Synaptic specificity is thought to arise from a code of specific interactions among adhesive molecules acting across the synaptic cleft. However, if a synaptic code does indeed exist, it is not known how it works, which synaptic molecules are involved, how they connect to each other, or their structures. The PIs will develop a high-throughput (HTP) program aimed at building an experimentally-validate protein interaction network of synaptic proteins and exodomains. The protein interactions and functions discovered in this project will provide a more comprehensive and unified view of the synaptic protein interaction network, which will enable the scientific community to determine whether a synaptic code may exist. New molecular pathways will be uncovered. These efforts to characterize the synaptic protein interaction network will provide innovative insights into brain circuit formation, and likely result in totally unexpected discoveries. These results will broadly inform cellular and molecular neurobiology and open the door to many interdisciplinary follow up studies.","FID":51}},{"geometry":{"x":-1.3552046578114472E7,"y":4658091.962381059,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: \"ECOSTIM-MR\"-Novel Multimodal Approach for High-Resolution Brain Research","Organization":"University of California-Davis","City":"Davis","State":"CA","Abstract":"A Novel Multimodal Approach for High-Resolution Brain Research<br /><br />The objective of this research program is to develop a novel methodology and analytic strategy for simultaneous high-density intracranial electrophysiological recording, electrical brain stimulation, and optogenetic activation/deactivation during high-field functional magnetic resonance imaging, and to apply this integrated methodology to investigate neural mechanisms that mediate sensory processing and selective attention in macaque. The project will advance discovery and understanding while promoting teaching and training by involving graduate students and postdoctoral scholars in undergraduate research supervision related to the project. Because selective attention is a core cognitive process, elucidating attentional mechanisms close relatives to humans such as the macaque remains a high priority in efforts to understand, diagnose and treat psychiatric conditions that involve deficits in attention, such as attention deficit hyperactivity disorder (ADHD), autism, obsessive compulsive disorder (OCD) and schizophrenia. <br /><br />All of our conscious perceptions and cognitive actions depend critically on the neural computations performed by cortical circuits, the network of connections made by neurons in the cerebral cortex. Given the central importance of cortical circuits in mediating complex behavior, it is critical that we have the tools necessary to study these circuits during behavior. No single method of recording brain activity is yet able to characterize both the functional anatomy and rapid temporal changes in neuronal activity with both high spatial and temporal resolution. However, by the integration of different methods with either high temporal or high spatial resolution, this research will develop tools capable of providing a view of the time course and functional anatomy of brain circuits supporting behavior.","FID":52}},{"geometry":{"x":-1.3721633332646206E7,"y":5553303.964744645,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Collaborative Research: BRAIN EAGER: Stretchable graphene transistors for high signal, high channel count neural recording","Organization":"Oregon State University","City":"Corvallis","State":"OR","Abstract":"This award is jointly made by two programs the Instrument Development for Biological Research program (IDBR) and Emerging Frontiers (EF) in the Directorate of Biological Sciences (BIO).<br /><br />A key roadblock to expanding our knowledge of the brain is that existing tools to probe its function are simply not up to the enormity of the task. Techniques for recording neural signals allow at most signals from tens or hundreds of neurons to be recorded, when thousands or even millions are needed. To address this challenge, improved types of sensors are required that record neural activity with greater signal quality and are more suited to parallel recording than current approaches. This collaborative project will develop a new type of sensor based on flexible graphene transistors. Graphene is an atomically thin sheet of carbon atoms that exhibits desirable physical, chemical, and electrical properties for interfacing with biological systems. However, the use of graphene transistors for single neuron sensing is largely unexplored. Open questions include the nature of the contact between the neuron and the graphene, the ultimate strength of electrical signals, and the long-term biocompatibility of graphene-based electrodes in the brain. Our proposed work will address these fundamental questions. If successful, this project will ultimately lead to societal benefits such as better neural prosthetics and new treatments for neurological disorders. Training opportunities at the interface of nano- and neuroscience, a key area of need for America?s technological future, will be available for graduate students.<br /><br /> 100% without degrading their electrical properties. The current project will investigate the electrical and mechanical interactions between kirigami graphene and individual neurons. Graphene will be cut into different patterns to optimize the mechanical contact between graphene and single neurons. Wrapping of graphene on the neuron will be maximized and the graphene will be used to measure voltage spikes produced by individual neurons, both in vitro and in vivo. With optimized conformal contact between graphene and neurons it will be possible to measure a large fraction of the intracellular potential (~ 70 mV). The semiconducting properties of graphene will also be used to amplify the bioelectronic signals to robust levels to facilitate multiplexed detection of thousands of neuron signals.","FID":53}},{"geometry":{"x":-1.3630214041027764E7,"y":4548523.63544689,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Development of Robotic Microscopy to monitor the longitudinal molecular dynamics of single neurons and circuits in situ in mammalian brain","Organization":"The J. David Gladstone Institutes","City":"San Francisco","State":"CA","Abstract":"This project is directed at developing a novel technology, robotic microscopy (RM), to \"bridge multiple spatial, temporal, and organizational scales to provide fundamental insights into the emergent properties of neural circuitry that ultimately lead to behavior and cognition.\" There are two primary benefits of the proposed studies. First, the experiments will result in the development of an RM instrument that can monitor the molecular dynamics of individual neurons in slices of living brain tissue over weeks at a time. Second, the experiments will use RM to study for the first time how learning and memory change the fundamental properties of specific neurons in situ to enhance synaptic plasticity, providing new insights into the mechanisms involved in learning and memory. In the past, RM was used to study neurons in culture. The primary activity in the proposed studies will be to validate the utility of RM to monitor neuronal dynamics in brain slices that maintain their natural physiological connectivity and architecture. Other benefits will be access of the scientific community to a technology that can examine the biochemistry of neurons and other cell types longitudinally and the development of new instrumentation that can be used in academic courses that teach students, postdoctoral fellows and research scientists novel imaging approaches to study brain circuits.<br /><br />The problem to be addressed is whether RM can be used to study neurons expressing the Arc gene in situ in hippocampal brain slices. Arc is important for long-term memory consolidation and synaptic plasticity, and its activity is greatly enhanced in specific neuron populations by stimuli that affect learning. The methods to be employed will involve the use of novel Arc genetic probes and transgenic mice to determine if RM can identify selective Arc-expressing neurons activated in brain slices by long-term potentiation (LTP) and long-term depression (LTD) or in brain in vivo during learning and memory consolidation. The goals of the studies will be to determine if different Arc neuronal circuits mediate LTP and LTD, and if the same Arc expressing neurons activated in vivo in the brain during learning can be monitored by RM in situ in brain slices. The scope of the studies will determine if RM can identify and study different Arc neuronal circuits activated in vitro and in vivo by different forms of learning and memory consolidation.","FID":54}},{"geometry":{"x":-7913248.982685472,"y":5215375.350743217,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Massive-scale multi-area single neuron recordings to reveal circuits underlying short-term memory","Organization":"Massachusetts Institute of Technology","City":"Cambridge","State":"MA","Abstract":"This award is jointly made by two programs: Instrument Development for Biological Research program (IDBR), and Emerging Frontiers (EF), in the Directorate of Biological Sciences (BIO).<br /><br />Short-term memory is a crucial component of cognitive function and pervades nearly all aspects of our mental lives. Previous research has shown that short-term memory involves multiple cognitive components and diverse brain regions. However, it is not mechanistically understood what regions are involved when, what neuronal subsets are recruited within these regions, or how they interact to represent information relevant to behavior. This proposal aims to elucidate the role of visual, association, and motor cortex in mice performing a visually-cued short-term memory task. This will be accomplished using massive-scale two-photon calcium imaging in behaving mice to measure activity of thousands of neurons simultaneously across these multiple brain regions. Subsequently, optogenetic manipulation of brain regions and of computationally identified neuronal assemblies will be used to determine their causal role in behavior. These technologies and results will have wide impact on understanding neural circuits underlying behavior and cognition. New approaches will be introduced for massive-scale mapping of single neuron activity in relation to a quantifiable behavior. New ways to determine circuit connectivity, and novel combination computational and optogenetic technologies to manipulate critical circuit components, will be introduced. These large data sets will be made widely and freely available, enabling other research groups to avail of these data for novel analyses.<br /><br />The goal of this proposal is to develop novel tools and provide unprecedented information on neuronal activity patterns and circuits in order to understand the role of multiple cortical areas during short-term memory in mice. Classical electrophysiological recordings are limited to relatively small numbers of neurons with unknown identity. In addition, while microstimulation or pharmacological manipulations can be used to activate or inhibit all the neurons within a local area, it is not possible to selectively excite or inhibit specific neuronal subpopulations that are known to play a role in the behavior. The proposal addresses these issues by developing novel tools to study mice performing a visually-cued memory-guided discrimination task. First, methods for massive scale imaging (up to ten thousand neurons simultaneously) of multiple cortical regions spanning several millimeters in the mouse cortex will be developed. Second, mice will be trained on a visually cued short-term memory task with suitable behavioral richness, including separate sensory, memory and response epochs, so that activity in distributed cortical regions (such as visual, parietal, and frontal motor cortices) can be imaged and the role of individual areas in each epoch can be ascertained. Third, targeted inactivation of specific brain areas will be performed to determine their role in the behavior. Finally, computationally identified neuronal subsets in specific areas will be stimulated in order to determine if they are sufficient for altering behavior. Together, these will be the first studies in the field to link behavior, extremely large-scale multiple-area recordings, and causal manipulations of areas and identified neuronal assemblies. By introducing tools for a radically different approach from previous analyses of memory and memory-guided functions, it is expected that the project will have a significant impact on the field.","FID":55}},{"geometry":{"x":-1.3552543418798326E7,"y":4657977.306838632,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"BRAIN EAGER: Monitoring the Function of Individual Synaptic Contacts during Circuit Plasticity with Novel Optogenetic Sensors","Organization":"University of California-Davis","City":"Davis","State":"CA","Abstract":"One of the primary challenges in neuroscience is to understand how sensory experiences drive the changes in brain circuits that underlie learning. Notably, the current lack of adequate tools to monitor the functional properties of individual synaptic connections has been holding back efforts to define how complex neuronal firing patterns drive changes in neuronal connectivity in the brain. This EAGER proposal is focused on the development and application of radically novel fluorescent probes to visualize integrated neural activity at individual synapses. If successful, these innovative probes will be transformative for the field; broad application of these probes by the neuroscience community will enable discovery of the rules that link sensory-driven neural activity to the structural changes in synaptic connectivity underlying learning. This knowledge would revolutionize current understanding of the dynamic changes in brain structure and function during learning. Furthermore, this project will foster close collaboration between groups of investigators with complementary expertise, and thus will create a vibrant environment for interdisciplinary training of the next generation of scientists. <br /><br />This EAGER proposal addresses one of the major unsolved problems in neuroscience: how complex patterns of neural activity at multiple synapses interact to drive experience-dependent changes in circuit connectivity. The specific goal is to develop and apply novel fluorescent probes for visualizing the history of neural activity at individual synapses. These innovative probes will facilitate mapping the function and structure of the neural circuitry underlying a specific physiological process or behavioral task. To accomplish this goal, a multidisciplinary approach will be used that incorporates genetic strategies, computation-guided protein design, two-photon imaging, and electrophysiology. First, candidate sensors will be generated through a high-throughput, multi-step sensor screening process. Next, the sensitivity and kinetics of the sensors will be characterized in neurons in vitro, ex vivo, and in vivo. Finally, the sensors will be implemented in brain slices to probe the activity-dependent mechanisms that drive the formation and stabilization of synaptic connections. Ultimately, these sensors will be used to define the activity-dependent mechanisms that drive circuit changes in vivo during complex behavioral tasks. The proposed research would provide much needed imaging tools of synaptic activity that are compatible with a variety of advanced imaging techniques, such as wide-field, confocal and two-photon microscopy, and would dramatically enhance understanding of how the history of neural activity at individual synapses and their neighbors can influence long-term stability of neural circuit connections.","FID":56}},{"geometry":{"x":-8254894.670579214,"y":4974568.965801979,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"MRI: Development of FNIRS Equipment for Assessing Functional Connectivity in Brain Injury","Organization":"New Jersey Institute of Technology","City":"Newark","State":"NJ","Abstract":"PI: Alvarez, Tara<br />Proposal: 1428425<br />Title: MRI: DEVELOPMENT OF FNIRS EQUIPMENT FOR ASSESSING FUNCTIONAL CONNECTIVITY IN BRAIN INJURY<br /><br />Significance<br />This project can have a large impact. There are many clinical populations including: TBI, stroke, multiple sclerosis, autism, neurodegenerative disorders and aging, which could be studied with the proposed equipment and integrated platform. The PIs were the first to study fMRI and eye movements in vision rehabilitation in mTBI, which can potentially impact the health care management of vision dysfunction. Functional brain connectivity and eye movements show promise as potential biomarker(s) to quantitatively measure neurological function in such clinical issues as moderate traumatic brain injury (mTBI) in athletes and soldiers, as well as in children with vision dysfunction and mTBI. <br /><br />The PIs will integrate this platform into their signal processing and instrumentation courses. The PIs have a history of outreach activities previously funded through an NSF CAREER award and the NIH. All those activities will continue, which include: mentorship of under-represented grade school, high school, undergraduate, and graduate (Masters and Ph.D.) students.<br /><br />Technical Description<br />This proposal requests funding to design an integrated, portable functional near infrared spectroscopy instrument (fNIRS) that was successfully developed with Vision and Neural Assessment Equipment. The system will have the following capabilities: 1) custom software with user-friendly script language to program independent and multiple visual stimuli, 2) simultaneous recording of functional connectivity with fNIRS and eye movement responses, 3) library of visual stimuli for other clinicians to use and 4) data analysis algorithms to determine potential brain connectivity measures or biomarkers that are sensitive and specific in identifying neurological and visual deficits. This transformative project will enable basic and clinical research scientists to assess brain functions in normal and impaired populations.","FID":57}},{"geometry":{"x":-1.3167919521798773E7,"y":4031572.7612343263,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"INSPIRE: Bioelectronic Systems for Investigating Neural Plasticity","Organization":"University of Southern California","City":"Los Angeles","State":"CA","Abstract":"PI: Weiland, James D.<br />Proposal: 1343193<br />Title: Bioelectronic Systems for Investigating Neural Plasticity<br /><br />This INSPIRE award brings together research areas traditionally supported by the Biophotonics and Nanobiosensing programs in the Chemical, Bioengineering, Environmental, and Transport Systems Division (CBET) of the Engineering Directorate (ENG); the Neural Systems program in the Integrative Organismal Systems (IOS) Division of the Biological Sciences Directorate(BIO); the Cognitive Neuroscience program in the Behavioral and Cognitive Sciences Division (BCS) of the Social, Behavioral and Economic Sciences Directorate (SBE); the Physics of Living Systems program in the Physics Division of the Mathematical & Physical Sciences Directorate (MPS).<br /><br />Significance<br />The formation of connections in the human brain is driven by experience. Particularly in development, but also in adulthood, repeated activity leads to lasting changes at the synaptic level. Understanding the mechanisms behind synapses formation and modification remains a fundamental question in neuroscience. To enable novel experiments that will expand our basic understanding of plasticity, the PIs propose to create and test bioelectronics systems designed specifically for neuroscience experiments. This approach is transformative because it sheds the usual constraints applied to bioelectronics systems, which are almost uniformly designed for human use. By focusing from this beginning on the need for systems to enable novel, fundamental neuroscience experiments, this interdisciplinary team will create bioelectronics implants optimized for investigating basic questions underlying plasticity. <br /><br />Technical Description<br />An ultraminiaturized bioelectronics system capable of both stimulation of and recording from nerve cells will be utilized. The system will feature novel approaches to integrated circuit design, wireless operation information transfer, microelectromechanical systems for integration of the circuit with tissue, and materials for improved neural interfaces. System power will be provided by a rechargeable microbattery, allowing the system to be completely implanted and the animal to be untethered and freely roaming across several meters of experimental space. These systems will allow extended periods of bioelectronic stimulation as well as multi-animal experiments. Visual cortex plasticity in response to bioelectronic retinal input will be investigated in long-term studies with frequent monitoring of visual cortex anatomy using two-photon microscopy. Different mouse knockout models that either increase plasticity or decrease plasticity will be utilized to thoroughly investigate anatomical changes driven by bioelectronic input. Experiments related to hippocampal neurophysiology will be conducted to precisely measure activity at the neural level and compare this activity to recorded behavior. From this, sophisticated multi-input, multi-output models can be created that explain the behavior.","FID":58}},{"geometry":{"x":-8257646.403597482,"y":4969676.995991726,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"MRI - Head Injury Biomechanics Measurement System","Organization":"New Jersey Institute of Technology","City":"Newark","State":"NJ","Abstract":"PI: Pfister, Bryan J.<br />Proposal: 1428925<br />Title: MRI - Head Injury Biomechanics Measurement System<br /><br />Significance<br />Mild traumatic brain injuries (TBI) and concussions are currently a major public health concern that dominates our lives from adolescent activities to professional sports to everyday falls. An estimated 1.6 to 3.8 million sports-related concussions occur in US alone. Though there are many research efforts to describe and treat concussion medically, trauma to the head is essentially a biomechanical problem. The PIs have extensive experience with TBI and blast brain trauma research. They believe that the problem can be defined by specifying the biomechanical boundary value problem through prescribing the right geometry and material and initial/boundary conditions through carefully conducted experiments and modeling. The head injury biomechanics measurement system will enable the PIs to control and measure the biomechanical parameters that bound concussive conditions. This effort will lead in developing a Brain Injury Criterion (BIC) similar to the development of the Head Injury Criterion for automotive accidents. This effort will fill the important fundamental knowledge gap in current traumatic concussive brain injury research.<br /><br />Technical Description<br />The major goal of both PIs and the Center for Injury Biomechanics, Materials and Medicine (CIBM3) is to provide a link between external loading of the head to the spatial and temporal stress and strains that cause injury to the brain. The Head Injury Biomechanical Measurement System proposed here is an enabling component that will allow researchers to precisely replicate the injury event, accurately measure stresses and strains at multiple discrete locations and help develop bio-fidelic computer models to establish the relationship between external loading and tissue level state of stress. This will be important to researchers internationally to replicate clinically relevant biomechanical injury parameters in their models to investigate the traumatic mechanisms of concussive injury.<br /><br />The proposed Head Injury Biomechanical Measurement System will be a unique system in the academic research community. This unique research approach of using cadavers in addition to physical dummy models will add clinical relevance towards developing a BIC and the potential to be a standard in the field.","FID":59}},{"geometry":{"x":-9322836.568464404,"y":5203330.773584212,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Emergence of Geometric Order and Cell Identity in the Cone Photoreceptor Mosaic","Organization":"University of Michigan Ann Arbor","City":"Ann Arbor","State":"MI","Abstract":"Animals begin their life by undergoing a remarkable process of self-organization: Starting from a tiny, single-celled egg, they develop into an incredibly complex organism. Moreover, they do so without centralized control. No master builder directs each cell to its correct position in the final body plan. How exactly living cells are able to collaborate to create precisely constructed tissues and organs is the central question of developmental biology. This project will study a particular example of such self-organization in the fish eye. It will use a combination of approaches, including observations of eye organization, perturbation of this organization by laser pulses, and computer simulations. These techniques will provide a deeper understanding of the fish eye system. This fundamental knowledge about biological self-organization has potential applications ranging from new disease treatments to the design of synthetic self-organizing systems inspired by the mechanisms at work in the eye. As a collaboration between a physicist and a biologist, the project will create opportunities for interdisciplinary education at many levels. The investigators will place a special emphasis on involving students from traditionally underrepresented backgrounds in research early in their undergraduate careers.<br /><br />The project will combine biological experiments with mathematical modeling to study the emergence of the striking crystalline arrangement of cone photoreceptor cells in the zebrafish retina. The guiding hypothesis is that the formation of this ordered lattice depends on anisotropic mechanical stresses imposed on the retinal epithelium by the annular ligament, a rigid ring of tissue that surrounds the retinal margin. Prior work has shown that a mathematical model of the interaction between mechanical forces and planar cell polarity can reproduce many of the observed features of the regular arrangement of cones, and, in particular, the model correctly predicted the presence of strongly anisotropic interactions between cells in perturbed retina. The current project will test the guiding hypothesis directly. The investigators will use new transgenic strains generated on a pigment mutant background to perform the first imaging and laser microsurgery of retinas in living, adult fish. This will provide a fine-grained quantitative characterization of the degree of mosaic order in space and time. Then, the investigators will observe how this order is affected by ablation of the annular ligament and the photoreceptor cells, using microsurgery to measure stress anisotropy in the retina.","FID":60}},{"geometry":{"x":-1.0612846007520458E7,"y":3469584.977050416,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"SCH: EXP: Collaborative Research: Exploring Sparsity and Spectral-Temporal Decomposition in Real-Time Network Modulation for Intractable Epilepsy","Organization":"William Marsh Rice University","City":"Houston","State":"TX","Abstract":"Understanding the relationship between brain activity and human behavior is not only one of the most important scientific challenges of our generation but also one of the most important challenges in medicine and public health. This project develops new technology that can address the minute size of the neurons, and the vast amount of data generated by neural activity. This project leverages the collaborative environment between Rice and Texas Medical Center to develop novel electrical stimulation approaches to modulate the seizure network, adaptively and selectively. If successful, the end result would be a reparative therapy that leverages inherent brain plasticity mechanisms and may one day be independent of chronically implanted electronics.<br /><br />This project develops algorithms that capture the dynamic, frequency dependent connectivity of the brain from real-time monitoring of the brain using ECoG (Electrocorticography) and then identifying the \"optimal\" parameters of the LFS (low-frequency electrical stimulation) to modulate the connectivity of the epilepsy network with temporal and spatial precision. The complexity of modeling such connectivity in real-time is managed by first segmenting neural activity into different epochs and spectral bands and then deriving the sparse connectivity in each of the segments. Effective connectivity in each spectral-temporal segment is estimated using Granger causality. LFS is applied after detecting interictal epileptiform discharges (IEDs) at spatial locations identified from the model. These critical steps lead to the development of a prototype system of real-time stimulation with a natural trade-off of complexity versus accuracy prompting a compromise between battery life and efficacy. The efficacy of spatially-optimized, activity-triggered LFS is evaluated by measuring the irritability of the seizure network and comparing the rate of IEDs detected during pre- and post-treatment periods. These experiments would point the way to treatment of pharmacologically refractory epilepsy without surgical resection of brain tissue and lead to reparative therapies leveraging inherent brain plasticity. The proposed methodology presents the first of its kind reparative, real-time, and selective network modulation to treat a debilitating disease.","FID":61}},{"geometry":{"x":-1.0616667858934717E7,"y":3469584.977050416,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"SCH: EXP: Collaborative Research: Exploring Sparsity and Spectral-Temporal Decomposition in Real-Time Network Modulation for Intractable Epilepsy","Organization":"University of Texas Health Science Center Houston","City":"Houston","State":"TX","Abstract":"Understanding the relationship between brain activity and human behavior is not only one of the most important scientific challenges of our generation but also one of the most important challenges in medicine and public health. This project develops new technology that can address the minute size of the neurons, and the vast amount of data generated by neural activity. This project leverages the collaborative environment between Rice and Texas Medical Center to develop novel electrical stimulation approaches to modulate the seizure network, adaptively and selectively. If successful, the end result would be a reparative therapy that leverages inherent brain plasticity mechanisms and may one day be independent of chronically implanted electronics.<br /><br />This project develops algorithms that capture the dynamic, frequency dependent connectivity of the brain from real-time monitoring of the brain using ECoG (Electrocorticography) and then identifying the \"optimal\" parameters of the LFS (low-frequency electrical stimulation) to modulate the connectivity of the epilepsy network with temporal and spatial precision. The complexity of modeling such connectivity in real-time is managed by first segmenting neural activity into different epochs and spectral bands and then deriving the sparse connectivity in each of the segments. Effective connectivity in each spectral-temporal segment is estimated using Granger causality. LFS is applied after detecting interictal epileptiform discharges (IEDs) at spatial locations identified from the model. These critical steps lead to the development of a prototype system of real-time stimulation with a natural trade-off of complexity versus accuracy prompting a compromise between battery life and efficacy. The efficacy of spatially-optimized, activity-triggered LFS is evaluated by measuring the irritability of the seizure network and comparing the rate of IEDs detected during pre- and post-treatment periods. These experiments would point the way to treatment of pharmacologically refractory epilepsy without surgical resection of brain tissue and lead to reparative therapies leveraging inherent brain plasticity. The proposed methodology presents the first of its kind reparative, real-time, and selective network modulation to treat a debilitating disease.","FID":62}},{"geometry":{"x":-1.3168072395855343E7,"y":4032069.60191818,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Retinal Nanophotoswitch","Organization":"University of Southern California","City":"Los Angeles","State":"CA","Abstract":"Proposal: 1404089<br />PI: Humayun, Mark S.<br />Title: Retinal Nanophotoswitch<br /><br />Significance <br />The objective of the proposed research is to develop a novel neurophotonic molecular switch for light-activation of neurons. A visual prosthesis based on this nanophotoswitch (NPS) has the potential to improve the visual acuity for the millions of patients suffering from retinal degenerative diseases, such as retinitis pigmentosa and age-related macular degeneration. This proposal is very innovative. The biophysical mechanism is completely differentiated from electrical devices and other molecular photo-switch-based approaches. Beyond vision restoration, it is a generally useful approach for controlling excitable cells. If successful, it may have a great impact on patients who are underserved by current treatments. <br /><br />The interdisciplinary research provides excellent educational opportunities for participating graduate and undergraduate students. The proposing team has an exceptional record on inclusion of women, under-represented minorities, and undergraduates in their research. They also have a good track record on outreach to the local community, and planned outreach activities include Research Experience for Teachers and activities for K-12 students.<br /><br />Technical Description <br />Nanophotoswitch (NPS) offers a new tool to elicit electrical activity for basic science studies of neuronal function, both in vitro and also potentially in vivo. The hypothesis is based on the NPS design and results of pilot experiments, that light induces an electrical dipole in the NPS. Preliminary data indicate that an NPS based on ruthenium bipyridine (Rubpy) inserts into cell membranes and upon visible-wavelength illumination triggers action potentials in cultured excitable cells and in wholemount rat retina. When injected into the eye of blind photoceptor-degenerate rats, visual stimulation induces electrical activity in the superior colliculus. It was also demonstrated that NPS can both depolarize or hyperpolarize the membrane, depending on the environmental redox potential. This unique combination of bi-directional modulation of the membrane potential in one biophotonic switch affords the ability to both activate and inhibit the action potential firing of the illuminated cells with the same molecule, presenting largely increased flexibility in neuronal control. The NPS would be useful in studying any electrically excitable cell, including, for example, cardiomyocytes, smooth muscle cells, neuroendocrine cells, and certain glial and cancer cells. Since light-activated signaling unit is individual neurons, a visual prosthesis based on NPS system has the potential to provide higher visual acuity for the millions of patients with photoreceptor loss due to retinal degenerative diseases, such as retinitis pigmentosa (RP) and age-related macular degeneration (AMD). Distinct from other nano-scale optical cellular modulating approaches using optogenetics or azobenzene-based photoswitches, this approach obviates the need for gene manipulation, toxic ultraviolet illumination or immunogenic molecules, due to the unique light-to-electrical signal transduction mechanism of the NPS.","FID":63}},{"geometry":{"x":-9761210.516633373,"y":5169525.167058042,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Biological links between rhythm and reading","Organization":"Northwestern University","City":"Evanston","State":"IL","Abstract":"Learning to read is the cornerstone of education. Recently, it has been discovered that the better you are at keeping a beat (e.g., accurately tapping along to a metronome or tapping out a beat in music) the better you are at reading. This raises fundamental questions about the overlapping brain and behavioral bases of reading and rhythmic abilities. This project measures sound-induced brainwaves in the auditory neural system in a search for \"neural signatures\" that are shared between people who are good readers and those who are good at keeping a beat. Once these signatures are established, they can be used to hone programs such as school-based music instruction that emphasize rhythmic skills in order to best encourage the parts of the brain that support reading and literacy.<br /><br />The investigators will examine the overlap in the neural resources drawn upon by reading and rhythm. By measuring neural responses they will test the hypothesis that two types of rhythmic skills, synchronizing to a metronomic beat and extracting a beat from a complex rhythm, involve different brain regions, subcortical and cortical, respectively. The hypothesis is that the two rhythmic skills relate to temporal precision in the brainstem and phase-locking of ongoing cortical oscillations and contribute independent sources of variance to reading ability. By comprehensively testing rhythmic and reading skills in secondary school students, an age group old enough to perform the required rhythmic tasks but in whom reading skills are continuing to emerge, the investigators hope to further our understanding of reading and rhythm in relation to the unique contributions of subcortical and cortical auditory areas. In so doing, this work might guide the development of teaching strategies to optimize language skills for all children and remediation programs for poor readers.","FID":64}},{"geometry":{"x":-1.246081634442127E7,"y":3951920.6135265934,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"III: Small: Multi-modal Neuroimaging Data Fusion and Analysis with Harmonic Maps Under Designed Riemannian Metric","Organization":"Arizona State University","City":"Tempe","State":"AZ","Abstract":"The rapid development in acquiring multi-modal neuroimaging data provides exciting new opportunities to systematically characterize human brain structure, its relationship to cognition and behavior, and the contributions of genetic and environmental factors to individual differences in brain circuitry. To optimally use such rich multi-modal data, there is an urgent need for powerful computational frameworks to integrate and analyze multi-source data. The current practice usually combines available data features from different sources without considering the intrinsic geometry and biology structure relationship between data sources. Shape analysis based approach may serve as a bridge for a general and integrative approach to multi-model data fusion and analysis. Although numerous studies have been devoted to imaging data registration research, limited progress has been made to integrate different modality data with some physically nature and geometrically intrinsic structures. This proposal focuses on investigating and developing computational algorithms on harmonic map with prescribed Riemannian metric, and on producing theoretically sound and practically efficient solutions for general multi-modal data fusion and analysis problems. The work outlined in this proposal will have applications in a number of research fields, including (1) Shape Analysis, neuroimaging and medical imaging in general. The proposed research unifies and connects a variety of computational geometry techniques and tackles a few open problems making it an ideal framework for teaching concepts in shape analysis as well as providing students a broader context in which various components may fit together. The algorithms and tools developed in this project will have a direct impact on neuroimaging research. It may enable discovery of multi-modal imaging biomarkers for some neurodegenerative disease, such as Alzheimer's disease. Harmonic maps and their related methods have applications in many other fields, including medical imaging, computer vision, machine learning, computer graphics, and geometric modeling. The PI will make the software tools accessible to the society. This project will facilitate the development of new courses and laboratory infrastructure for neuroimaging research. It also provides a unique opportunity for students from computer science to learn neuroscience more efficiently. The funding will allow continuation of ongoing efforts to actively recruit and advise students from under-represented groups.<br /><br />An integrated research and education plan is outlined in this project to investigate and develop computational theorems and algorithms. The first goal is to develop a method to compute the harmonic map under a designed Riemannian metric between general surfaces. One key novelty is that the new method formulates multi-source information with a Riemannian metric and thus the multi-source fusion problem is converted to compute a surface harmonic map which is adapted to any designed Riemannian metric on the target surface. Next, a variational formulation that optimizes the diffeomorphic harmonic map via adjusting the Riemannian metric will be developed. The harmonic map guarantees that it has the global minimum deformation. It will be a practical way to optimize diffeomorphisms between surfaces and provide the flexibility to introduce general objective functions defined by other data sources. In addition, an algorithm for volumetric harmonic maps under a designed Riemannian metric and a set of novel multivariate geometry statistics for multi-source data analysis will be implemented. The framework explores multi-source data fusion with intrinsic geometry structures and the multivariate statistics may provide more sensitive, reliable and accessible brain imaging biomarkers for neuroimaging analysis. The anticipated outcomes of this research project are: (1) new computational algorithms on harmonic maps with significant applications in various fields, such as medical imaging, computer vision, machine learning, computer graphics and geometric modeling; (2) a practical software package with a rigorous mathematical foundation to analyze multi-modal data and produce sensitive and comprehensive multivariate imaging statistics. It will be tested on a large public neuroimaging dataset and evaluated by various classification tasks.","FID":65}},{"geometry":{"x":-8754614.556747502,"y":4273288.195136842,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"CHS: Small: A Hybrid Brain-Computer Interface for Behaviorally Non-Responsive Patients","Organization":"North Carolina State University","City":"Raleigh","State":"NC","Abstract":"Brain-computer interfaces (BCIs) have been explored for several years in an effort to provide communication for \"locked in\" users who have the desire and mental capacity to communicate but are unable to speak, type, or use conventional assistive technologies due to severe motor disabilities, and a lot of work has gone into making this initially crude technology more practical, usable, accurate, and flexible (e.g., by improving speed of performance and providing virtual reality feedback and/or advanced device control). In this project the PI and his team turn their attention to a group with even greater need: patients who have been misdiagnosed as vegetative or minimally conscious, and without the mental ability to form messages or respond to questions. These individuals are not only unable to move but also unable to see, and are at risk of being euthanized based on the mistaken assumption that they are effectively \"brain dead\" whereas it has been shown by European colleagues, using methods and equipment comparable to American hospitals, that 17-42% of such patients were in fact able to use a BCI to respond to questions. The PI worries that severely injured veterans and others might sometimes be misdiagnosed, potentially able to communicate with friends and loved ones if only some technology could more effectively assess their brain activity. The PI's goal in this project is to extend current BCI technologies to focus on assessing consciousness in this vulnerable patient population and provide, where possible, the ability to communicate.<br /><br />The PI's approach is to adapt and extend conventional BCI protocols and feedback environments to work with people who cannot see and must instead rely on other modalities of stimulation. The work will involve three thrusts. First, the PI and his team will improve methods to identify brain response based only on tactile and auditory stimuli, by determining the best tactile stimulation frequency for each subject. Second, they will use \"hybrid\" BCIs combining P300s and steady state somatosensory evoked potentials (SSSEPs) to elicit two different kinds of EEG signals that could improve accuracy. Finally, they will develop a new six choice BCI system tailored for these users; at present the best BCIs for these patient groups allow just two or three choices, whereas a six choice system could lead to faster communication and broader control options. Across all three of these thrusts, the team will also explore signal processing methods to improve accuracy. Human subjects experiments will be conducted across three groups: healthy blindfolded users, healthy blind persons, and patients who have been labeled as nonresponsive. Project outcomes, which will include useful non-visual BCIs that have been tested with blind persons and new methods for combining different EEG signals to improve performance, will be broadly disseminated both to the scientific community and to those involved with nonresponsive patient care at all levels.","FID":66}},{"geometry":{"x":-9823221.006585788,"y":4882551.874623969,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Cognitive and neurocognitive individual differences in native and nonnative language processing","Organization":"University of Illinois at Urbana-Champaign","City":"Champaign","State":"IL","Abstract":"High proficiency in multiple languages provides economic advantages, as linguistic flexibility in business and government discourse facilitates communication in an increasingly globalized world. However, the ability to reach high levels of proficiency and fluency in a second language (L2) during adulthood is notoriously variable, with individuals showing marked differences in the rate of L2 acquisition and the eventual level of proficiency. A complete understanding of the roots and implications of these differences - including documenting individual differences in the brain mechanisms supporting nonnative language comprehension and learning - is crucial for the development of targeted language instruction methods and interventions. Such targeted interventions can lead to tangible gains in language learning outcomes. Moreover, emerging research now shows that even monolinguals show systematic, qualitative individual differences in the neural mechanisms responsible for language comprehension. However, as with L2 learning, the causes and consequences of these differences are poorly understood.<br /><br />The investigators will use a multidimensional approach to investigate individual differences in language comprehension and language learning across several populations: monolinguals, classroom-instructed L2 learners of Spanish, and Spanish-English bilinguals in the United States. The research will combine novel behavioral and brain-based measures of language processing, cognitive executive functions, and cortical organization for language. The investigators will link these with measures of language proficiency and language experience to isolate the cognitive, neural, linguistic, and experiential factors related to differences in how individuals build interpretations during the course of sentence comprehension. In particular, electroencephalographic recordings during language comprehension and executive processing will allow the investigators to document how these processes unfold in the brain millisecond-by-millisecond. Novel multivariate statistical models will be used to identify factors related to how different individuals make use of semantic and grammatical cues during reading. The aim is to elucidate the cognitive, neural, and linguistic bases of individual differences in language learning and language comprehension, and tie them closely to a neurobiological model of language. As such, the findings will have clear and practical implications for language training.","FID":67}},{"geometry":{"x":-8235148.000924025,"y":4975450.19447355,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Social Identity and Person Perception","Organization":"New York University","City":"New York","State":"NY","Abstract":"Social identity, or perceived memberships in relevant social groups, can influence a wide range of processes, including how we perceive, evaluate, and interact with others. The proposed research examines the role of group membership on person perception, theorizing that it will be easier to perceive in-group members as having their own thoughts, goals and feelings relative to members of other groups. This is important, as the ability to infer states in others can facilitate social interactions, appropriate responding to others' emotions, and the perception that others have moral rights and responsibilities. Conversely, when people do not perceive others as having their own thoughts, goals and feelings, they may be more likely to respond with prejudice and discrimination. Therefore, this work has the potential to provide new ways of understanding how group identity influences perceptual processes, suggest novel techniques to reduce real world prejudice and discrimination, and to improve cooperation between members of different groups.<br /><br />Jay Van Bavel (New York University) will conduct a series of studies to examine how perceptions of others are influenced by individuals' group identity (e.g., team membership, national identity). The research team will examine this question in relation to: [1] the importance people place on their group memberships and whether people believe that their group is threatened by an out-group; [2] the neural systems that underlie this relationship; [3] how biases against an out-group affect behavior (e.g., aggression, intergroup conflict, and care); and [4] methods to reduce bias against out-groups. By examining these factors, this proposed research will result in new theorizing about the role of social identity on perceptions of others.","FID":68}},{"geometry":{"x":-1.3553040259482179E7,"y":4657633.34021135,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"III: Small: Collaborative Research: Functional Network Discovery for Brain Connectivity","Organization":"University of California-Davis","City":"Davis","State":"CA","Abstract":"Neuroscience is at a moment in history where mapping the connectivity of the human brain non- invasively and in vivo has just begun with many unanswered questions. While the anatomical structures in the brain have been well known for decades, how they are used in combination to form task specific networks has still not been completely explored. Understanding what these networks are, and how they develop, deteriorate, and vary across individuals will provide a range of benefits from disease diagnosis, to understanding the neural basis of creativity, and even in the very long term to brain augmentation. Though machine learning and data mining has made significant inroads into real world practical applications in industry and the sciences, most existing work focuses on lower-level tasks such as predicting labels, clustering and dimension reduction. This requires the practitioner to shoe-horn their more complex tasks, such as network discovery, into the algorithm's settings. <br /><br />The focus of this grant is a transition to more complex higher-level discovery tasks and in particular, eliciting networks from spatio-temporal data represented as a tensor. Here the spatio-temporal data is an fMRI scan of a person represented as a four dimensional tensor with each entry in the tensor being a data point that indicates the brain activity at that time and location. The overall problem focus is to simplify this data into a cognitive network consisting of identifying active regions of the brains and the interactions that occur between them. The work will consist of three intertwined tasks as follows: i) Supervised and Semi-supervised Network Discovery, ii) Complex Network Discovery and iii) Network Discovery in Populations. In the supervised/semi-supervised setting, the networks discovered involves coordinated activity among some combination of anatomical structures Since all or some of the structures are given along with their boundaries, this is termed a supervised (or semi-supervised) problem. With complex network discovery the team will move beyond finding a single network of coordinated activity to finding multiple networks with complex (beyond coordinates) relationships between the structures/regions. Finally with network discovery in populations , the previous work that studies an individual scan will be expanded to a population of scans. A population may be a collection of individuals performing the same task or a single individual's scans collected over time. Studying such populations allows addressing innovative questions such as: \"How does one individual's network change over the course of development, aging, or disease?\" and \"How do the networks differ for one group of individuals to that of another group?\"","FID":69}},{"geometry":{"x":-8780709.75908107,"y":5294551.080217878,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"NRI: Human Cognition Assisted Control of Industrial Robots for Manufacturing","Organization":"SUNY at Buffalo","City":"Buffalo","State":"NY","Abstract":"Advanced manufacturing, driven by industrial robots, is playing an increasing role in US economy. Robots are being used to carry out assembly, welding, material handling and fabrication. Even as such interactions are becoming more common in every phase of manufacturing, a perfect symbiotic relationship between machines and human beings is still very far away. Because of this, a majority of the robotic applications in manufacturing are currently limited to areas where a relatively low level of skill is required. This has restricted the full potential of robotics to augment human operators and improve productivity and quality of life. With recent advances in cognitive neuroscience and brain interface technologies, connecting the human cognitive thought process directly to robots and machines is possible, resulting in direct control of real world applications. By collecting the brain signals using sensors and analyzing the thought processes, many activities that take place inside the brain when humans take specific actions or think of actions can be identified and matched to known signals using fast computation. This new human-robot communication paradigm will be demonstrated by developing three manufacturing scenarios. The project will also have broad applicability in the design of robotic systems in fields outside manufacturing, including telesurgery, rehabilitation and space exploration. Results from this multidisciplinary research, which combines manufacturing, computer science and robotics, have the potential to improve the productivity of future manufacturing plants and can lead to new commercial ventures, which will help the US maintain global leadership in robotics and manufacturing, broaden participation of underrepresented groups in research, and positively impact engineering education.<br /><br />Significant future challenges in the development of a new human-robot communication system, which allows operators to perform complex high skilled tasks, will be addressed. The postulated paradigm will be explored by meeting the following intellectual challenges: (i) researching a novel methodology for communicating motion commands to a robot by imagining simple actions using a grammar called \"actemes,\" (ii) new brain-computer mode and algorithms to classify these actemes and, (iii) an intent-based system that auto-completes robotic actions based on most likely sequence of events that human operators are planning to complete. Three robotic manufacturing scenarios will be explored to demonstrate the human cognition based interactions in manufacturing environment: assembly, direct control, and quality control through object recognition. Finally, by using a non-invasive brain-computer interface a wide range of day-to-day applications of robotics will be demonstrated.","FID":70}},{"geometry":{"x":-1.3167346244086634E7,"y":4032470.8963166764,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Understanding biological motion","Organization":"University of California-Los Angeles","City":"Los Angeles","State":"CA","Abstract":"A major issue in the psychological sciences is how people can infer the intentions of others. Humans are remarkably adept at predicting the actions of other people and making inferences about their intention and goals. The present investigation examines how humans make such inferences from the physical movements of others. The work is guided by a computational theory of biological motion understanding that quantifies the action representations that allow people to make inferences in action recognition and prediction. The larger goal is to explain how perception and reasoning operate synergistically to infer hidden goals and intentions. <br /><br />The proposed research has broad impact in several domains. The inference capacity of most people exceeds that of today's best machine vision systems. For example, in the investigation of the bombing at the Boston marathon, extensive video from surveillance camera systems was available but it was the trained human eye that led to arrests. Human investigators scrutinized hundreds of hours of videos frame by frame and identified suspects who displayed suspicious behavioral patterns. Hence, understanding how humans make inferences and predictions about actions will play an important role in guiding the development of more advanced machine vision systems, useful in forensic sciences as well as many other real-world applications. In addition, individuals with autism or nonverbal learning disabilities often show difficulty in inferring the meaning of observed actions. Investigation of the key computational components underlying action understanding may potentially guide the development of behavioral interventions to facilitate compensatory strategies for understanding actions.","FID":71}},{"geometry":{"x":-9675183.248071702,"y":4928779.101711621,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"Collaborative Research: A behavioral and computational investigation of the generality and transferability of category representations","Organization":"Purdue University","City":"West Lafayette","State":"IN","Abstract":"How people acquire and use different types of knowledge is a fundamental issue in cognitive science, applicable to problems in education, training, and the development of expertise. For example, learning to categorize types of materials (such as natural vs. synthetic, or polymers vs. ceramics) can be accomplished using textbooks, but it can also be accomplished with hands on experience in the field. Different types of training likely lead to different forms of knowledge, and the form of knowledge may constrain how, and in what situations, the knowledge can be used. Thus, the best way to train a person may differ depending not only on the type of information being learned, but also on the situations in which the knowledge will need to be used. The investigators will examine how to promote the learning of different forms of knowledge in different situations. They will also investigate the neural and computational bases of the differences in forms of knowledge in order to develop a unifying theory of how knowledge acquisition and application varies across situations in predictable ways. A larger goal is to determine how knowledge, once learned, can be transferred to new situations. This project will advance scientific understanding of human knowledge acquisition and its use. The project also has the potential to foster the development of new tools that may improve the training of students and professionals.<br /><br />Categorization researchers have made an enormous contribution to the understanding of the many ways in which knowledge can be represented and used. A current challenge facing the field of categorization, and cognitive science more generally, is how to best integrate these findings with the broader goal of understanding the extent to which different types of knowledge representations generalize to new situations. The proposed research utilizes a combination of behavioral, neuroimaging, and computational modeling techniques to address these challenges. Specifically, the investigators will explore (1) the factors influencing the development of different types of category representations, (2) the psychological functions and brain networks supporting category representations, and (3) the utility of different types of category representations for supporting performance in new tasks and/or with new stimuli. In addition, this research will highlight important relationships between machine learning techniques and methods used in cognitive science. As a result, the research should be of broad interest to psychologists, computer scientists, and the general cognitive science community.","FID":72}},{"geometry":{"x":-8368727.258699195,"y":4862220.924627769,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"WORKSHOP: Quantitative Theories of Learning, Memory, and Prediction","Organization":"University of Pennsylvania","City":"Philadelphia","State":"PA","Abstract":"The development of quantitative theories of learning, memory, and prediction is fundamental to understanding human cognitive processing. This workshop, to take place in Arlington VA, May 8-9, 2014, tackles a key scientific need: to integrate modern complex systems and network approaches with understanding cognitive function. Predictive models of higher order cognitive processes could inform the development of neuroprosthetics, facilitate advances in brain-computer interfaces, and assist in the construction of intervention protocols for cognitive deficits that accompany neurological disorders and psychiatric disease. <br /><br /><br />Understanding how the human brain works has emerged as a major international focus of research in the coming decade, identified as such in President Obama's State of the Union Address in February 2013 and further developed in President Obama's BRAIN initiative announced on April 2, 2013. This workshop will bring together systems neuroscientists, cognitive scientists, applied mathematicians, and theoretical physicists. The aim is to identify a set of achievable goals that integrate dynamic, quantitative theories of cognition with neuroscientific and theoretical avenues of research.","FID":73}},{"geometry":{"x":-7965154.011281364,"y":5084002.257438966,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"WORKSHOP: Neurobiology of Cognition: Circuits, dynamics, action and perception GRC & GRS","Organization":"Gordon Research Conferences","City":"West Kingston","State":"RI","Abstract":"There has been an explosion of information in molecular, cellular, circuit and systems neuroscience but little of that information has made significant inroads into our understanding of cognitive function. This Gordon Research Conference on the Neurobiology of Cognition should help bridge the gap, at the very least by identifying the avenues for connection that have the most potential for near-term traction and by linking scientist from disparate fields. <br /><br />The conference will take place in Newry, ME on July 20-25, 2014. The emphasis of the workshop is to facilitate in-depth discussion between scientists working in divergent fields whose integration is essential to understanding the neurobiology of cognition. NSF support will enable graduate students and postdoctoral trainees to participate in this high-profile workshop and will allow early stage investigators (non-tenured) to attend as speakers and full participants.","FID":74}},{"geometry":{"x":-1.3609280091927977E7,"y":4562103.72425037,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Title":"AF: Medium: Algorithmic Explorations of Networks, Markets, Evolution, and the Brain","Organization":"University of California-Berkeley","City":"Berkeley","State":"CA","Abstract":"Computer science is not just the scientific discipline behind the information technology revolution; it is also an apt framework for understanding the world around us. This project is about applying the point of view of algorithms -- and their antithesis, complexity -- to understanding phenomena and challenges in a variety of domains, including the Internet, markets, evolution, and the brain. To understand the Internet and the networks and markets it entails and enables, one must combine algorithms with ideas from economics and game theory. This research will focus on online markets and particularly their dynamic (that is, multi-stage) nature, on incentives for improving congestion in network routing and air traffic, on algorithms for propagating influence in social networks, as well as new kinds of algorithms that take their inputs from competitors (who may choose to misrepresent their data). The PI will continue his research on how computational insights can shed light on some key problems in evolution, including certain rigorous connections between natural selection, machine learning, and a problem in Boolean logic. Finally, the PI will work to reconcile learning algorithms with new insights from neuroscience.<br /><br />The project includes research on certain crucial problems at the interface between computation and game theory/economics/networks, while continuing past work employing computational concepts to elucidate evolution and, more recently, neuroscience. The PI will study the important problem of dynamic mechanism design in economics from the point of view of computational complexity and approximate implementation. He will also study mechanisms for managing congestion, with possible applications to air traffic control. The project will explore the computational and graph-theoretic properties of several novel and promising game-theoretic models of network creation. It will study from the complexity standpoint Nash equilibria with continuous strategies, and extensions of the Nash equilibrium concept beyond utility theory. The project will also explore new and timely modes of computation in which all inputs (ultimately, all computational components) are provided by selfish rational agents. In evolution, the PI will explore the connections between learning algorithms, games, and natural selection, and a different connection between Boolean satisfiability and the emergence of novelty. The PI also plans to develop a new genre of learning algorithms that are more faithful to the new insights we are gaining into the brain. Finally, from the standpoint of algorithms and complexity, the PI will look at several computational problems ranging from network variants of the set cover problem to linear programming and optimizing multivariate polynomials.","FID":75}}],"geometryType":"esriGeometryPoint"},"nextObjectId":76,"popupInfo":{"title":"{Title}","fieldInfos":[{"fieldName":"Title","label":"Title","isEditable":true,"tooltip":"","visible":true,"stringFieldOption":"textbox"},{"fieldName":"Organization","label":"Organization","isEditable":true,"tooltip":"","visible":true,"stringFieldOption":"textbox"},{"fieldName":"City","label":"City","isEditable":true,"tooltip":"","visible":true,"stringFieldOption":"textbox"},{"fieldName":"State","label":"State","isEditable":true,"tooltip":"","visible":true,"stringFieldOption":"textbox"},{"fieldName":"Abstract","label":"Abstract","isEditable":true,"tooltip":"","visible":true,"stringFieldOption":"textbox"},{"fieldName":"FID","label":"FID","isEditable":false,"tooltip":"","visible":true,"format":{"places":0,"digitSeparator":true},"stringFieldOption":"textbox"}],"description":"<b>{Organization}<\/b><div><i>{City}, {State}<br /><\/i><div><br /><\/div><div>{Abstract}<br /><\/div><\/div>","showAttachments":false,"mediaInfos":[]}}],"showLegend":true},"visibility":true,"opacity":1},{"layerType":"ArcGISFeatureLayer","id":"featColl_7611","title":"Intelligence Advanced Research Projects Activity","featureCollection":{"layers":[{"layerDefinition":{"currentVersion":10.3,"id":0,"name":"IARPA_Brain_Investments","type":"Feature Layer","displayField":"","description":"","copyrightText":"","defaultVisibility":true,"relationships":[],"isDataVersioned":false,"supportsCalculate":true,"supportsAttachmentsByUploadId":true,"supportsRollbackOnFailureParameter":true,"supportsStatistics":true,"supportsAdvancedQueries":true,"supportsValidateSql":true,"supportsCoordinatesQuantization":true,"advancedQueryCapabilities":{"supportsPagination":true,"supportsQueryWithDistance":true,"supportsReturningQueryExtent":true,"supportsStatistics":true,"supportsOrderBy":true,"supportsDistinct":true},"geometryType":"esriGeometryPoint","extent":{"type":"extent","xmin":-1.3595624876999998E7,"ymin":4033707.103500003,"xmax":-7915484.3912,"ymax":6053547.287299996,"spatialReference":{"wkid":102100,"latestWkid":3857}},"drawingInfo":{"renderer":{"type":"simple","symbol":{"color":[46,139,87,255],"size":9,"angle":0,"xoffset":0,"yoffset":0,"type":"esriSMS","style":"esriSMSCircle","outline":{"color":[0,0,128,255],"width":0,"type":"esriSLS","style":"esriSLSSolid"}}},"labelingInfo":null},"allowGeometryUpdates":true,"hasAttachments":false,"htmlPopupType":"esriServerHTMLPopupTypeNone","hasM":false,"hasZ":false,"objectIdField":"FID","globalIdField":"","typeIdField":"","fields":[{"name":"Institution","type":"esriFieldTypeString","alias":"Institution","sqlType":"sqlTypeNVarchar","length":256,"nullable":true,"editable":true,"domain":null,"defaultValue":null},{"name":"City","type":"esriFieldTypeString","alias":"City","sqlType":"sqlTypeNVarchar","length":256,"nullable":true,"editable":true,"domain":null,"defaultValue":null},{"name":"State","type":"esriFieldTypeString","alias":"State","sqlType":"sqlTypeNVarchar","length":256,"nullable":true,"editable":true,"domain":null,"defaultValue":null},{"name":"Program_Name","type":"esriFieldTypeString","alias":"Program Name","sqlType":"sqlTypeNVarchar","length":256,"nullable":true,"editable":true,"domain":null,"defaultValue":null},{"name":"Program_Description","type":"esriFieldTypeString","alias":"Program Description","sqlType":"sqlTypeNVarchar","length":256,"nullable":true,"editable":true,"domain":null,"defaultValue":null},{"name":"FID","type":"esriFieldTypeInteger","alias":"FID","sqlType":"sqlTypeInteger","nullable":false,"editable":false,"domain":null,"defaultValue":null}],"indexes":[],"types":[],"templates":[],"supportedQueryFormats":"JSON","hasStaticData":false,"maxRecordCount":-1,"capabilities":"Query,Editing,Extract"},"featureSet":{"features":[{"geometry":{"x":-8311589.379000001,"y":4918441.043700002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Institution":"Siemens Corporation","City":"Princeton","State":"NJ","Program_Name":"Knowledge Representation in Neural Systems","Program_Description":"The KRNS program seeks insights into the brain's representation of conceptual knowledge. 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the Olfactory Code\" and is jointly funded by the Chemistry of Life Processes program in the Chemistry Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Physics of Living Systems program in the Physics Division, the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Division of Biological Infrastructure, and the Division of Emerging Frontiers. The sense of smell is essential for maintaining quality of life in humans, and its decline can be an important harbinger of neurodegenerative disease. Moreover, since nearly all animals aside from primates rely on olfaction for most survival functions, understanding chemical sensing has immense practical value, for example, in the control of agricultural pests or in training animals to detect odors relevant for bomb, drug and cancer detection. In spite of its importance, the understanding of olfaction lags far behind the other senses, which is in part due to the lack of understanding of the physical space of odors. The understanding of the neural bases of vision and audition were greatly advanced by investigations of the physical dimensions of visual and auditory stimuli. It is therefore likely that a similar in-depth investigation of odor space - how natural odors occur and the backgrounds against which they must be detected - will reveal a new depth of richness of neural representations of odors in the brain. Insects such as the fruit fly and honey bee are excellent models for this research because of the accessibility of their central nervous systems, because of their ease of use under controlled laboratory conditions, and because of the functional similarity of how odors are processed in insect and mammalian brains. This research will characterize how odor flowers and fruits with respect to behavioral value for honey bees (food) and fruit flies (food and egg laying sites). Further monitoring of neural activity in early and later stage processing in the brain, when combined with computational modeling, will reveal significantly richer neural representations than have heretofore been described. This new understanding stands to have an impact on understanding how healthy brains encode sensations and memories of odors and how brains fail under disease conditions. It will also have an impact on understanding how the sense of smell may be built into engineered devices. Finally, both insects are also of economic importance to agriculture for crop pollination (honey bees) and damage to fruit (fruit flies). The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. <br /><br />This research will quantitatively characterize the real-world statistics of multi-component natural odor scenes and investigate how they drive behavior and processing in several brain regions. The focus will be on honey bee as well as fruit fly adults and larva as models, where it will be possible to characterize a library of ethologically relevant natural odors associated with a diversity of behavioral outputs. The work will begin by quantitatively characterizing the detailed statistical properties of natural odor scenes in defined ethological contexts. This will build on the rich literature on identified natural odors in insects and mammals. Naturally occurring plant and fruit odor samples from the natural environments of each insect will be collected and chemically analyzed. Nonlinear dimensionality reduction techniques and approaches based on sparse coding will determine the dimensions of odor space that are most salient for behavioral decisions. Such a quantitative deconstruction of the sensory input would be unprecedented in olfactory neuroscience, and should allow the PIs to effectively and comprehensively drive olfactory circuits for the first time. The hypothesis is that the stimulus dimensions that are most behaviorally relevant to the animal will be most efficiently extracted by the olfactory system. Synthetic odor blends will be specially constructed to vary along relevant sensory dimensions, to probe neural codes and adaptive behaviors in the olfactory system. As in research on the visual system, analysis of such evoked neural responses using statistical methods that take into account natural odor statistics will reveal novel olfactory computations and behaviors that have been previously inaccessible. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering and biology.","FID":3}},{"geometry":{"x":-1.24608163074E7,"y":3951920.762199998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Arizona State University","Title":"Planning Grant: Collaborative Research: I/UCRC for Building Reliable Advances and Innovation in Neurotechnology (BRAIN)","City":"Tempe","State":"AZ","Abstract":"This project will bring together teams from Arizona State University and University of Houston in collaboration with industry partners to establish a research center, called BRAIN (Building Reliable Advances and Innovation in Neurotechnology) that will overcome several innovation challenges in neurotechnology: 1) The pace of innovation exceeds the rate of evaluation for acceptable performance; 2) Standards and regulatory science for rigorous validation of safety, efficacy, and long-term reliability are missing; 3) Lack of open access to technologies and synergistic collaborations impede transfer of novel technologies to the market; and 4) Current technologies are costly, limiting their utility in enhancing treatment and overcoming physical disabilities. In addition, the BRAIN Center, through the efforts of the Education/Outreach coordinator, will work to rectify under-representation in the science, technology, engineering, and math (STEM) fields by broadening new participation and retaining current participants in STEM through 1) newly initiated K-12 outreach programs that expose aspiring STEM participants to innovative neurotechnologies, 2) undergraduate internship program within the Center that targets specific student organizations (e.g., Society of Mexican-American Engineers and Scientists, Society of Women Engineers), and 3) focusing on problems in the neurological space that affect underrepresented groups disproportionately. <br /><br />The Center's vision is a synergistic, interdisciplinary approach to the development and validation of affordable patient-centered technologies, and use of those technologies in understanding neural systems. BRAIN will leverage expertise in neural, cognitive and rehabilitation engineering, robotics, clinical testing, and reverse-translational research at Arizona State University (ASU) and the University of Houston (UH) to (a) enhance the rate of development and empirical validation of new technologies through partnerships with industry leaders and other strategic partners; (b) develop standards and test technologies in human and non-human models using a multi-scale approach ranging from single neurons to organismal systems; (c) characterize novel and innovative technologies such as biosensors and quantitative analysis tools for systems and behaviors; (d) evaluate the impact of these technologies on quality of life; and (e) reduce the cost burden of neural technologies on hospitals and families.","FID":4}},{"geometry":{"x":-1.3555152625500001E7,"y":4534581.493600003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Lawrence Livermore 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dysfunction","FID":12}},{"geometry":{"x":-1.36276917937E7,"y":4547988.378899999,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Micropet, Inc.","Title":"Revolutionizing Prosthetics","City":"San Francisco","State":"CA","Abstract":"Develop advanced prosthetic arm systems and methods for restoration of near-natural movement and control","FID":13}},{"geometry":{"x":-1.3151759756299999E7,"y":4048618.4927999973,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"California Institute Of Technology","Title":"Ideas Lab Collaborative Research: Using Natural Odor Stimuli to Crack the Olfactory Code","City":"Pasadena","State":"CA","Abstract":"This project was developed during a NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Chemistry of Life Processes program in the Chemistry Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Physics of Living Systems program in the Physics Division, the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Division of Biological Infrastructure, and the Division of Emerging Frontiers. The sense of smell is essential for maintaining quality of life in humans, and its decline can be an important harbinger of neurodegenerative disease. Moreover, since nearly all animals aside from primates rely on olfaction for most survival functions, understanding chemical sensing has immense practical value, for example, in the control of agricultural pests or in training animals to detect odors relevant for bomb, drug and cancer detection. In spite of its importance, the understanding of olfaction lags far behind the other senses, which is in part due to the lack of understanding of the physical space of odors. The understanding of the neural bases of vision and audition were greatly advanced by investigations of the physical dimensions of visual and auditory stimuli. It is therefore likely that a similar in-depth investigation of odor space - how natural odors occur and the backgrounds against which they must be detected - will reveal a new depth of richness of neural representations of odors in the brain. Insects such as the fruit fly and honey bee are excellent models for this research because of the accessibility of their central nervous systems, because of their ease of use under controlled laboratory conditions, and because of the functional similarity of how odors are processed in insect and mammalian brains. This research will characterize how odor flowers and fruits with respect to behavioral value for honey bees (food) and fruit flies (food and egg laying sites). Further monitoring of neural activity in early and later stage processing in the brain, when combined with computational modeling, will reveal significantly richer neural representations than have heretofore been described. This new understanding stands to have an impact on understanding how healthy brains encode sensations and memories of odors and how brains fail under disease conditions. It will also have an impact on understanding how the sense of smell may be built into engineered devices. Finally, both insects are also of economic importance to agriculture for crop pollination (honey bees) and damage to fruit (fruit flies). The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. <br /><br />This research will quantitatively characterize the real-world statistics of multi-component natural odor scenes and investigate how they drive behavior and processing in several brain regions. The focus will be on honey bee as well as fruit fly adults and larva as models, where it will be possible to characterize a library of ethologically relevant natural odors associated with a diversity of behavioral outputs. The work will begin by quantitatively characterizing the detailed statistical properties of natural odor scenes in defined ethological contexts. This will build on the rich literature on identified natural odors in insects and mammals. Naturally occurring plant and fruit odor samples from the natural environments of each insect will be collected and chemically analyzed. Nonlinear dimensionality reduction techniques and approaches based on sparse coding will determine the dimensions of odor space that are most salient for behavioral decisions. Such a quantitative deconstruction of the sensory input would be unprecedented in olfactory neuroscience, and should allow the PIs to effectively and comprehensively drive olfactory circuits for the first time. The hypothesis is that the stimulus dimensions that are most behaviorally relevant to the animal will be most efficiently extracted by the olfactory system. Synthetic odor blends will be specially constructed to vary along relevant sensory dimensions, to probe neural codes and adaptive behaviors in the olfactory system. As in research on the visual system, analysis of such evoked neural responses using statistical methods that take into account natural odor statistics will reveal novel olfactory computations and behaviors that have been previously inaccessible. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering and biology.","FID":14}},{"geometry":{"x":-1.31630087882E7,"y":4035986.888899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Los Angeles","Title":"Collaborative Research: Analysis of the Mammalian Olfactory Code","City":"Los Angeles","State":"CA","Abstract":"This project was developed during a NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Chemistry of Life Processes program in the Chemistry Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Physics of Living Systems program in the Physics Division, the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Division of Biological Infrastructure, and the Division of Emerging Frontiers.<br /><br />The mammalian sense of smell is arguably the most complex sensory system in the animal kingdom. Hundreds of olfactory receptors are deployed to detect a vast array of chemicals with exquisite sensitivity in complex environments. This collaborative project combines biochemistry, neurobiology, genomics, mathematics and new technologies to understand how the mammalian olfactory system detects, encodes and extracts meaning from chemical stimuli. The goals of this project are to: (1) elucidate fundamental neural mechanisms for how chemical sensation turns into the perception of a smell; (2) produce a vast array of scientific resources to olfactory scientists; (3) provide valuable information for broader audiences, including for molecular evolution, chemical ecology, and flavor and fragrance communities; (4) establish new technologies and mathematical frameworks to study biological systems; and (5) facilitate applied chemical sensing technologies for environmental monitoring, food safety, and homeland security. The project also offers training opportunities from the high school to the postdoctoral trainee level, and educational opportunities and outreach through partnerships with local science museums as well as science learning centers and their media outlets.<br /><br />This project's efforts are organized around three aims that focus on how information about odor identity and odor valence (attractiveness/aversiveness) is encoded at the level of olfactory receptors (Aim 1); within the olfactory bulb, where odor information is first processed (Aim 2); and the cortical amygdala, where odor codes may integrate with other information streams (Aim 3). Completion of the project entails the development and use a broad array of innovative approaches that include mapping all human and mouse odorant receptors to the chemicals they bind, defining the innate valence of these chemicals using behavioral assays, mapping all odorant receptor projections to the olfactory bulb, functionally characterizing their neural representations in the olfactory bulb and cortical amygdala, and using novel mathematical approaches to understand the underlying structure of odor coding and olfactory neural circuits at the level of sensory neurons, olfactory bulb glomeruli, and amygdala. Progress towards each aim involves close collaborations between team members with diverse expertise, including molecular biology, behavioral neuroscience, in vivo functional imaging, and mathematical and theoretical analysis of complex datasets. The multidisciplinary strategy implemented here promises to lead to an integrated and comprehensive understanding of how mammals sense and make sense of their chemical environments.","FID":15}},{"geometry":{"x":-1.31216788652E7,"y":4009766.1240999997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"The Scripps Research Institute","Title":"Collaborative Research: Analysis of the Mammalian Olfactory Code","City":"La Jolla","State":"CA","Abstract":"This project was developed during a NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Chemistry of Life Processes program in the Chemistry Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Physics of Living Systems program in the Physics Division, the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Division of Biological Infrastructure, and the Division of Emerging Frontiers.<br /><br />The mammalian sense of smell is arguably the most complex sensory system in the animal kingdom. Hundreds of olfactory receptors are deployed to detect a vast array of chemicals with exquisite sensitivity in complex environments. This collaborative project combines biochemistry, neurobiology, genomics, mathematics and new technologies to understand how the mammalian olfactory system detects, encodes and extracts meaning from chemical stimuli. The goals of this project are to: (1) elucidate fundamental neural mechanisms for how chemical sensation turns into the perception of a smell; (2) produce a vast array of scientific resources to olfactory scientists; (3) provide valuable information for broader audiences, including for molecular evolution, chemical ecology, and flavor and fragrance communities; (4) establish new technologies and mathematical frameworks to study biological systems; and (5) facilitate applied chemical sensing technologies for environmental monitoring, food safety, and homeland security. The project also offers training opportunities from the high school to the postdoctoral trainee level, and educational opportunities and outreach through partnerships with local science museums as well as science learning centers and their media outlets.<br /><br />This project's efforts are organized around three aims that focus on how information about odor identity and odor valence (attractiveness/aversiveness) is encoded at the level of olfactory receptors (Aim 1); within the olfactory bulb, where odor information is first processed (Aim 2); and the cortical amygdala, where odor codes may integrate with other information streams (Aim 3). Completion of the project entails the development and use a broad array of innovative approaches that include mapping all human and mouse odorant receptors to the chemicals they bind, defining the innate valence of these chemicals using behavioral assays, mapping all odorant receptor projections to the olfactory bulb, functionally characterizing their neural representations in the olfactory bulb and cortical amygdala, and using novel mathematical approaches to understand the underlying structure of odor coding and olfactory neural circuits at the level of sensory neurons, olfactory bulb glomeruli, and amygdala. Progress towards each aim involves close collaborations between team members with diverse expertise, including molecular biology, behavioral neuroscience, in vivo functional imaging, and mathematical and theoretical analysis of complex datasets. The multidisciplinary strategy implemented here promises to lead to an integrated and comprehensive understanding of how mammals sense and make sense of their chemical environments.","FID":16}},{"geometry":{"x":-1.31216788652E7,"y":4009766.1240999997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"The Salk Institute For Biological Studies","Title":"Ideas Lab Collaborative Research: Using Natural Odor Stimuli to Crack the Olfactory Code","City":"La Jolla","State":"CA","Abstract":"This project was developed during a NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Chemistry of Life Processes program in the Chemistry Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Physics of Living Systems program in the Physics Division, the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Division of Biological Infrastructure, and the Division of Emerging Frontiers. The sense of smell is essential for maintaining quality of life in humans, and its decline can be an important harbinger of neurodegenerative disease. Moreover, since nearly all animals aside from primates rely on olfaction for most survival functions, understanding chemical sensing has immense practical value, for example, in the control of agricultural pests or in training animals to detect odors relevant for bomb, drug and cancer detection. In spite of its importance, the understanding of olfaction lags far behind the other senses, which is in part due to the lack of understanding of the physical space of odors. The understanding of the neural bases of vision and audition were greatly advanced by investigations of the physical dimensions of visual and auditory stimuli. It is therefore likely that a similar in-depth investigation of odor space - how natural odors occur and the backgrounds against which they must be detected - will reveal a new depth of richness of neural representations of odors in the brain. Insects such as the fruit fly and honey bee are excellent models for this research because of the accessibility of their central nervous systems, because of their ease of use under controlled laboratory conditions, and because of the functional similarity of how odors are processed in insect and mammalian brains. This research will characterize how odor flowers and fruits with respect to behavioral value for honey bees (food) and fruit flies (food and egg laying sites). Further monitoring of neural activity in early and later stage processing in the brain, when combined with computational modeling, will reveal significantly richer neural representations than have heretofore been described. This new understanding stands to have an impact on understanding how healthy brains encode sensations and memories of odors and how brains fail under disease conditions. It will also have an impact on understanding how the sense of smell may be built into engineered devices. Finally, both insects are also of economic importance to agriculture for crop pollination (honey bees) and damage to fruit (fruit flies). The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. <br /><br />This research will quantitatively characterize the real-world statistics of multi-component natural odor scenes and investigate how they drive behavior and processing in several brain regions. The focus will be on honey bee as well as fruit fly adults and larva as models, where it will be possible to characterize a library of ethologically relevant natural odors associated with a diversity of behavioral outputs. The work will begin by quantitatively characterizing the detailed statistical properties of natural odor scenes in defined ethological contexts. This will build on the rich literature on identified natural odors in insects and mammals. Naturally occurring plant and fruit odor samples from the natural environments of each insect will be collected and chemically analyzed. Nonlinear dimensionality reduction techniques and approaches based on sparse coding will determine the dimensions of odor space that are most salient for behavioral decisions. Such a quantitative deconstruction of the sensory input would be unprecedented in olfactory neuroscience, and should allow the PIs to effectively and comprehensively drive olfactory circuits for the first time. The hypothesis is that the stimulus dimensions that are most behaviorally relevant to the animal will be most efficiently extracted by the olfactory system. Synthetic odor blends will be specially constructed to vary along relevant sensory dimensions, to probe neural codes and adaptive behaviors in the olfactory system. As in research on the visual system, analysis of such evoked neural responses using statistical methods that take into account natural odor statistics will reveal novel olfactory computations and behaviors that have been previously inaccessible. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering and biology.","FID":17}},{"geometry":{"x":-1.31216788652E7,"y":4009766.1240999997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-San Diego","Title":"Bilateral BBSRC-NSF/BIO: Collaborative Research: ABI Development: Seamless Integration of Neuroscience Models and Tools with HPC - Easy Path to Supercomputing for Neuroscience","City":"La Jolla","State":"CA","Abstract":"This project is a collaboration between the University of California San Diego and Yale University to develop a science gateway for the computational neuroscience community. A gateway such as this helps improve our understanding of how the brain works by making it easier for neuroscientists to use complex digital models of brain cells and circuits in their research. Powerful software has been developed for building and using models, and on-line resources such as Open Source Brain (OSB), ModelDB, Neuroscience Information Framework (NIF), and OpenWorm have been created to help neuroscientists find existing models, collaborate in developing new ones, and share the results of their work with others. However, models are becoming too complex for the computer hardware that is available to most neuroscientists, resulting in a critical need to use high performance computing resources (HPC). This work extends an existing Neuroscience Gateway (NSG), which was developed with support from NSF to eliminate or reduce many of the technical and administrative difficulties that previously limited neuroscientists' access to HPC (http://www.nsgportal.org/). That said, NSG users must still log in, upload models, launch simulations, and download results--a process that involves many time-consuming, error-prone steps. The expanded NSG-R will eliminate these steps by enabling on-demand, automated communication between itself and familiar working environments including resources like OSB and others mentioned above, and even with neural simulation software running on neuroscientists' own laptop and desktop computers. <br /><br />This seamless access to HPC is implemented in NSG-R by a software infrastructure that uses REpresentational State Transfer (\"REST\", the R in NSG-R). NSG-R utilizes set of web services which expose the capabilities of NSG for access via publicly available application programmer interfaces. This will allow users of neuroscience resources such as OSB, ModelDB, NIF and OpenWorm to readily access HPC from their respective websites via NSG-R. This enhances the usefulness of NSG-R, other neuroscience resources like OSB, and widely used neural simulators such as NEURON, GENESIS, PyNN, NEST, Brian and MOOSE. It also results in greater research productivity and enables wider use of large scale computational modeling by scientists and students. NSG-R will accelerate progress in brain science, and have far-reaching beneficial effects on related fields such as robotics and engineering of adaptive and learning systems. It will widen opportunities for educational and career advancement in neuroscience and engineering. Furthermore, by removing barriers that traditionally have limited access to HPC, NSG-R levels the playing field for all students and researchers regardless of their institutional affiliation. NSG-R, a free and open neuroscience gateway infrastructure, will naturally be a ready entry point for students and researchers from historically underrepresented schools and colleges. NSG-R workshops will be hosted at minority serving institutions (MSI) and opportunities for students to do internships with the NSG-R team at the University of California San Diego will be provided.","FID":18}},{"geometry":{"x":-1.35988768517E7,"y":4501269.358099997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Stanford University","Title":"BRAIN EAGER: Genetic Access of Neuronal Populations Activated by Two Experiences in the Same Animal","City":"Palo Alto","State":"CA","Abstract":"The mammalian brain consists of hundreds of millions to billions of nerve cells (neurons) that form complex networks. How perception, cognition, and action are reflected by the activities of neurons is a central question in modern neuroscience. The investigators have previously developed a genetic method to mark neurons that are activated by a specific sensory experience or behavioral episode, so they can visualize their connections and measure their activities. In this research, the investigators will develop new methods to improve the signal-to-noise ratio to more effectively identify the active neurons, and to mark two separate experiences differentially in the same animal so they can directly compare physiological properties of two populations of neurons, such as those before and after learning. The success of these approaches will enable scientists to compare brain representations of different stimuli and behavior, and what changes occur after learning.<br /><br />The method used to mark active neurons (TRAP, for targeted recombination in active populations) utilizes the property of immediate early genes, whose transcription is activated by neuronal activity. This was achieved using mouse genetics to place a drug-inducible Cre recombinase under the control of immediate early gene promoters, such that experience in the drug-active period turns on Cre reporter transgenes permanently. This research will utilize a combination of viral transduction and mouse genetics to differentially label neurons that are activated by two separate experiences. In addition, a strategy of using light to locally silence inhibitory neurons will be used to enhance excitation-to-inhibition ratio, and thereby enhance TRAP efficiency, in a much narrower time window during the drug-active period. The new transgenic mice and viral vectors will be deposited in public repositories after validation.","FID":19}},{"geometry":{"x":-1.36110939041E7,"y":4561060.924000002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Berkeley","Title":"BRAIN EAGER: Going All Wireless to Establish Bats as The First Mammalian Model System for Vocal Learning","City":"Berkeley","State":"CA","Abstract":"The ability to learn a language is a core feature of humanity. Yet, the detailed mammalian brain mechanisms that subserve this complex learning process are poorly understood. The reason for this major gap of knowledge stems from a surprising fact: The vast majority of mammals, including non-human primates and all standard mammalian laboratory animal models, do not learn their language, that is, their vocalizations are innate. Hence, the mammalian neural circuits that support language learning have remained largely obscure. The goal of this proposal is to take the most direct approach towards bridging this gap and establish the bat as the first mammalian model system for studying the detailed brain mechanisms subserving vocal learning. To achieve this goal, all wireless behavioral and neural monitoring technology will be developed and implemented to track and analyze vocal and neural signals of bats in natural settings. In addition to the development of new neurotechnologies and establishment of a new model system, the project supports opportunities for students from diverse backgrounds to engage in research and for public science education. <br /><br />Language learning is a social learning process that occurs under natural conditions and its investigation requires approaches that preserve such settings. To satisfy this requirement, the project aims to develop an all-wireless experimental approach that alleviates many of the physical constraints that are imposed by standard tethered systems. The proposed approach combines novel methods for monitoring and measurement both the animal's behavior, as well as neural activity in relevant brain circuits on a broad range of timescales ranging from milliseconds to months. Taking this approach, the project aims to lay the groundwork for enabling a detailed description of the underlying neuronal dynamics that support vocal learning in the juvenile bat and thereby establish the bat as a mammalian model for investigation of the neurobiology of vocal learning. Considering the profound influence language has over our daily lives, the technologies developed and discoveries made in this research program will be of major interest to both the broad neuroscience community as well as to the general public.","FID":20}},{"geometry":{"x":-1.31216788652E7,"y":4009766.1240999997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-San Diego","Title":"INSPIRE: Quantitative Estimation of Space-Time Processes in Volumetric Data (QUEST)","City":"La Jolla","State":"CA","Abstract":"This INSPIRE project is jointly funded by the Division of Advanced Cyberinfrastructure in the Directorate for Computer & Information Science, Physics of Living Systems in the Division of Physics in the Directorate for Math and Physical Science, Physical and Dynamic Meteorology in the Division of Atmospheric and Geospace Sciences in the Directorate for Geoscience, and the INSPIRE program in the Office of Integrative Activities.<br /><br />Advances in scientific instrumentation and computational hardware and software have resulted in an unprecedented ability to acquire, simulate, and visualize time resolved three-dimensional (3D) volumes of data, offering the promise of a greater understanding of complex systems previously beyond our technical grasp. However, as the size and complexity of these data increase, analyzing them becomes increasingly problematic, inhibiting scientific discovery and limiting the utility of the data acquired at great expense and effort. Two particularly cogent examples come from two seemingly disparate scientific fields: neuroscience and meteorology. Magnetic resonance imaging (MRI) scanners can now acquire functional MRI (FMRI) volumes of brain activity in almost real time, while mobile Doppler radar (MDR) systems are capable of acquiring time-dependent volumetric images of thunderstorms during tornado formation. In this project, entitled QUantitative Estimation of Space-Time processes in volumetric data (QUEST), the University of California, San Diego, Center for Scientific Computation in Imaging (CSCI), in partnership with the Center for Severe Weather Research (CSWR) and the Cooperative Institute for Meteorological Satellite Studies (CIMSS) will develop a novel framework for the analysis of time-varying 3D volumes, guided by large scale numerical simulations, to investigate two of the outstanding scientific questions of our age: What is the relationship between brain structure and function?, and How do strong, long-track tornadoes form? The resulting computational platform will be disseminated to the NSF community through the open source analysis and visualization platform (STK) to improve the ability of researchers to quantitatively analyze, visualize, and explore complex time varying volumetric datasets. <br /><br />This INSPIRE project develops advanced methods for automated quantitative characterization of subtle space-time patterns embedded within spatio-temporal data from 3D voxel-based digital imaging modalities based upon the team's recently formulated entropy field decomposition (EFD) theory, a probabilistic method efficiently that employs the information field theoretic approach with prior information supplied using the team's entropy spectrum pathways theory, in conjunction with numerical simulations designed both to constrain results to physically realizable solutions. The cross-disciplinary approach focuses on two outstanding problems in the respective fields of neuroscience and severe weather meteorology: 1) The identification of structural and functional modes of the human brain from high resolution anatomical MRI, diffusion tensor MRI, functional MRI data from the Human Connectome Project combined with numerical simulations of diffusion and functionally weighted MRI signals, and 2) The identification of signatures of tornado genesis and maintenance from MDR data from the Doppler-On-Wheels network in conjunction with tornado simulations using the CM1 model. Significant social impact would result from the ability to categorize states of brain activity in normal and diseased populations and the ability to reduce the lead time between tornado formation and warning to threatened populations. More generally, this novel methodology has the potential to transform the way analysis is conducted in a wide range of disciplines by enabling automated, quantitative detection of important, though perhaps subtle, variations in large, complex datasets undetectable by current traditional techniques.","FID":21}},{"geometry":{"x":-1.36110939041E7,"y":4561060.924000002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Berkeley","Title":"US-German Data Sharing: Integrating Distributed Data Resources to Enable New Research Approaches in Neuroscience","City":"Berkeley","State":"CA","Abstract":"This project seeks to develop new methods of describing and managing neuroscience data in order to accelerate scientific progress in many fields of neuroscience and deepen understanding of the brain. The project will produce software tools to enable annotation and integration of distributed data and help leverage the wealth of data emerging from current large-scale projects such as the Human Brain Project in Europe and the BRAIN Initiative in the US. These results will impact medical application areas such as brain machine interfaces, devices for sensor prosthetics and also application areas such as computer vision. Further, the methods developed might be generalizable to other domains of biology and medicine where traditional rigid approaches for organizing data are inapplicable. This could lead to the discovery of causes and treatments of diseases that would not have been made otherwise.<br /><br />Neurophysiology data, which contain recordings of brain activity, are becoming more commonly shared on the web but they are still very hard to use. To improve the usability of shared neurophysiology data sets, a standardized and expandable system will be developed for annotating the data with metadata required for their understanding. Furthermore, semantic web technology will be employed to represent, index, and integrate data and metadata, across distributed locations on the web. Improving the organization of metadata for shared neurophysiology data will be key for enabling studies that integrate across data sets, such as new types of meta-analyses or data mining methods. This project builds on existing online resources for neurophysiology data created by the project partners, CRCNS.org and G-NODE.org, and on pervious work by the INCF neurophysiology data sharing task force. Training of international students and researchers in annual summer courses at UC Berkeley and LMU Munich will improve career opportunities that allow individuals across disciplines to make discoveries and advancements in neuroscience. <br /><br />A companion project is being funded by the Federal Ministry of Education and Research, Germany (BMBF).","FID":22}},{"geometry":{"x":-1.31216788652E7,"y":4009766.1240999997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-San Diego","Title":"CHS: Small: A Novel P300 Brain-Computer Interface","City":"La Jolla","State":"CA","Abstract":"Brain computer interfaces (BCIs) translate basic mental commands into computer-mediated actions, thereby allowing the user to bypass the peripheral motor system and interact with the world directly via brain activity. These systems are being developed to aid users with motor deficits stemming from neurodegenerative disease, injury, or even environmental restrictions which make movement difficult or impossible. One of the most successful classes of EEG-driven BCI systems is the P300, which works by detecting user responses to flashed stimuli. In most P300 systems, a grid of letters and/or other symbols is presented and rows or columns of the symbols are flashed in random order; the user attends to the desired symbol (usually by silently counting when it flashes). A major problem with these grid-based P300 systems is that the user must ideally look at the flashed target and minimally attend to the tiny letters, but late-stage ALS and other locked-in patients for whom these systems are most needed have trouble foveating targets and making controlled eye movements. The PI's hypothesis is that a BCI that flashes segments of one large letter can retain the combinatorial efficiency that comes with querying several letters at once, while having the advantage of one central focus (no gaze shifts required). This research aims to design and test this new segment speller idea. Project outcomes have the potential to vastly improve the usability of P300 EEG-based BCI systems for those with visual, sensory and motor impairments. All software written for EEG signal processing and analysis will be made available as add-ons to EEGLAB which is distributed by the Swartz Center for Computational Neuroscience (SCCN) at UCSD and part of the Temporal Dynamics of Learning Center. Data will also be made available through the HeadIT data archive that is also run by the SCCN.<br /><br />This research task can be broken down into three main objectives: develop and test the response to flashed segments; improve the single-trial classification of the responses to flashed segments; and design a logic for selecting segments and interpreting their responses. The developed system will provide another method for BCI speller control that does not depend on the ability to shift gaze. The PI argues that this method will have a higher information transfer rate than other space invariant BCI spellers due to being able to probe multiple letters at once. Besides being advantageous for those with impaired eye movements and/or impaired vision, the method should have other advantages over the standard P300 systems. When errors are made, they will tend to be to visually similar symbols. Incorporating language priors and active segment selection is easily accommodated, and this may result in higher information transfer rates with slower flash rates. In addition the work on improving recognition of single-trial temporal EEG signals and incorporating Bayesian language models into spellers could be useful for other types of brain-computer interfaces.","FID":23}},{"geometry":{"x":-1.33248369745E7,"y":4085254.583999999,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Santa Barbara","Title":"SHF: Small: Development of Integrated Memristive Crossbar Circuits for Pattern Classification Applications","City":"Santa Barbara","State":"CA","Abstract":"Building artificial neural networks capable of matching the performance and functionality of their biological counterparts is one of the grand challenges in computing. The broad goal of this research project is to address one important aspect of this grand challenge, e.g., creating efficient hardware for implementing artificial neural networks. Artificial neural network based information processing, suitable for low precision applications, may indeed be particularly important in the present day context of energy efficient computing. If successful, this research has the potential to have broad and long lasting societal impact by improving energy efficiency and enriching functionality of existing electronics, and creating a large number of novel applications. The project will involve graduate and undergraduate students, include members of underrepresented groups and will thus help enlarge the workforce in information and communication technologies.<br /><br />The high complexity, connectivity and parallelism of neural networks make conventional technology hardware implementations rather inefficient. The core idea of this project is to utilize emerging memory devices, specifically memristors, which are essentially super-dense analog nonvolatile memory devices, to implement compact and energy efficient artificial neural networks. A particular experimental focus of the project is on demonstration of a hybrid memristive crossbar circuit implementation of small-scale (hundreds of neurons, thousands of synapses) multilayer perceptron performing pattern classification task. Although such a demonstration may only have a rather simple functionality, the resulting classifier would have all the key features of state-of-the-art deep learning convolutional neural network classifiers. The major focus is on the development of training algorithms compatible with memristor switching kinetics and investigation of the tradeoffs between complexity of hybrid circuits and classification performance. Theoretical modeling will guide experimental work towards most efficient implementations as well as ensure scaling of the approach to perform practical applications. Resolving hardware challenges for relatively simple neural networks would be essential for the development of more advanced neural networks capable of performing complex cognitive tasks.","FID":24}},{"geometry":{"x":-1.31630087882E7,"y":4035986.888899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Southern California","Title":"NCS-FO: Integrating neural interfaces and machine intelligence for advanced neural prosthetics","City":"Los Angeles","State":"CA","Abstract":"Brain-machine interfaces (BMI) read signals directly from the brain to control external devices such as robotic limbs. While this technology has great potential to benefit people who are paralyzed, BMIs often have poor performance because they use noisy, low-level signals to simultaneously control many aspects of the robotic limb's movements. In contrast, this project will address this shortcoming by reading high-level intents from the brain in order to control an intelligent robotic system. These changes reflect cutting-edge advances in neuroscience and machine intelligence and will require close cooperation between scientists, engineers, and physicians. The project aims to leverage expertise across these diverse fields in order to generate significant improvements in BMI technology to advance the national health, increase scientific understanding of the brain, and lead to dramatic improvements in the quality of life for these severely disabled persons.<br /><br />This collaborative project will decode high-level cognitive actions from neural signals recorded in the parietal cortex of a tetraplegic human, then carry out those intents using a smart robotic prosthesis. Persons with tetraplegia who have multielectrode arrays (MEA) implanted in reach and grasp areas of the posterior parietal cortex (PPC), will participate in experiments to explore the neural representation of cognitive intentions in human PPC including object selection, action intention, and neural control of robotic limbs. Experimental results will be used to construct BMI control algorithms optimized to decode these cognitive signals. In parallel, a modular, semi-autonomous robotic prosthesis will be developed that can identify household objects and plan reach-and-grasp movements to manipulate or transport the objects. These scientific and technological efforts will be supported by continued clinical care of the tetraplegic participants. The study will explore increasingly capable iterations of the BMI system, culminating in testing of the fully developed BMI system in the participants' own home environment where they will practice activities of daily living. The resulting system will leverage deep insights in cognitive neuroscience and advanced capabilities in machine sensing and robotic control systems to substantially improve the ease of use and capability of brain-machine interfaces.","FID":25}},{"geometry":{"x":-1.36110939041E7,"y":4561060.924000002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Berkeley","Title":"EAGER: Neural dust stimulation for closed loop neuromodulation","City":"Berkeley","State":"CA","Abstract":"Proposal No:1551239, EAGER-Neural dust stimulation for closed loop neuromodulation<br /><br />One of the most important challenges that remains in neuroengineering is the development and demonstration of a clinically viable neural interface which can both record from and stimulate many individual neurons and lasts a lifetime. These chronic or long-term neural interfaces are of increasing interest for both central (CNS) and peripheral nervous system (PNS) interventions. Creating lasting, durable, untethered interfaces raises a variety of issues, ranging from the nature of the physical substrate (avoiding the biotic and abiotic effects that presumably lead to performance degradation at the electrode-tissue interface, the density and spatial coverage of the sensing sites), the type of signals measured, and the computation and communication capabilities (how much signal processing on-chip data to transmit wirelessly) under the power budget of the whole system. This proposal seeks to extend our recently published Neural Dust platform to allow for stimulation of nerves via neural dust motes. We believe this to be an aggressive vision which would open the door to a vast array of interventions, including untethered neural recording of human nerves and neurons, untethered stimulation of these processes and record-and-stimulate closed loop systems. Such a vision will require a number of fundamental technological innovations that will have impact across domains including basic neuroscience, clinical interventions of neurological disorders, and prosthetics. For example, the ability to precisely monitor and modulate peripheral nerve activity with a minimally invasive medical device would enable a wide-range of therapeutic opportunities. This closed-loop neuromodulation cannot be done with existing technologies because they suffer from one of two major drawbacks: lack of spatial resolution or high degree of invasiveness. <br /><br />We recently proposed an ultra-miniature as well as extremely compliant system that could enable massive scaling in the number of recordings from the brain or the peripheral nervous system, providing a path towards truly chronic BMI. At the core of this vision is a platform for powering, receiving and transmitting information from inside a peripheral nerve to outside the body using aggressive, state-of-the-art circuit design and the recent demonstration of ultrasonic, piezocrystal \"neural dust? motes. The work envisioned in this proposal will leverage recent application specific integrated circuit (ASIC) technology to build stimulating motes that can address individual neurons (or peripheral fibers) and will demonstrate untethered stimulation of nerve fibers, paving the way to closed-loop record-and-stim technology using neural dust. This is a very aggressive, high risk direction which leverages existing neural dust developments with a very high potential payoff (as it enables untethered closed-loop neuromodulation systems). Our long term vision is a system capable of recording and stimulation in closed-loop.","FID":26}},{"geometry":{"x":-1.35988768517E7,"y":4501269.358099997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Stanford University","Title":"Collaborative Research: EAGER: Biomanufacturing: Bioengineering of 3-dimensional brain surrogate tissue models","City":"Palo Alto","State":"CA","Abstract":"PI: Demirci, Utkan<br />Proposal Number: 1547791<br /><br />PI: Kaplan, David L. <br />Proposal Number: 1547806 <br /><br />The coordinated function in the brain of billions of neurons in dense and entangled networks can be seen as the epicenter of our unique higher consciousness, as well as of our vulnerability to debilitating diseases, such as schizophrenia, autism and Alzheimer's. The investigators propose a unique approach of sound waves and silk protein biomaterials, to recreate the complex three-dimensional brain network structures in a small dish, and use them to investigate their response to a laboratory model of brain concussion damage. With these studies, the investigators aspire to demonstrate how these constructs may help scientists better understand the workings of the brain in healthy and diseased states.<br /><br />The complexity of the brain poses a large roadblock for scientists to examine molecular, cellular and circuit level behavior of brain physiology. Novel approaches and technologies are needed that complement and advance the existing in vivo, ex vivo and in vitro approaches. The goal of the proposed research is to develop a new flexible bioprinting platform for the in vitro fabrication of 3-dimensional (3D) neural tissue constructs that faithfully mimic the biological complexity, development, architecture and function of 3D circuits present in the brain. The key innovations include the strategy of acoustic biopatterning and silk protein scaffolds for encapsulating neurons in long-lived, 3D multilayered architectures. To prototype and validate the construct, the investigators propose in the first aim to create 6-layer cortical circuits built of primary neurons. In the second aim, they will examine the physiology of the 3D circuit tissues using a comprehensive neuro-technological tool-box. Electrophysiology, fluorescence imaging, genomics and proteomics approaches will be employed to evaluate functional and structural milestones of the developing in vitro 3-D neural circuits, including a brain damage disease model. This radically different approach for investigating brain physiology and pathophysiology has the potential to provide new tools for neuroscience, the utility of which extends to other fields because of the general applicability of the proposed advanced biomanufacturing approaches. The broader impact of this proposal includes the participation of high school, undergraduate and graduate level scientists in research at the intersection of neuroscience, tissue engineering and biomanufacturing, thus presenting a useful platform for the training of interdisciplinary scientists.","FID":27}},{"geometry":{"x":-1.3151759756299999E7,"y":4048618.4927999973,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"California Institute Of Technology","Title":"Collaborative: NCS-FO: Integrating neural interfaces and machine intelligence for advanced neural prosthetics","City":"Pasadena","State":"CA","Abstract":"Brain-machine interfaces (BMI) read signals directly from the brain to control external devices such as robotic limbs. While this technology has great potential to benefit people who are paralyzed, BMIs often have poor performance because they use noisy, low-level signals to simultaneously control many aspects of the robotic limb's movements. In contrast, this project will address this shortcoming by reading high-level intents from the brain in order to control an intelligent robotic system. These changes reflect cutting-edge advances in neuroscience and machine intelligence and will require close cooperation between scientists, engineers, and physicians. The project aims to leverage expertise across these diverse fields in order to generate significant improvements in BMI technology to advance the national health, increase scientific understanding of the brain, and lead to dramatic improvements in the quality of life for these severely disabled persons.<br /><br />This collaborative project will decode high-level cognitive actions from neural signals recorded in the parietal cortex of a tetraplegic human, then carry out those intents using a smart robotic prosthesis. Persons with tetraplegia who have multielectrode arrays (MEA) implanted in reach and grasp areas of the posterior parietal cortex (PPC), will participate in experiments to explore the neural representation of cognitive intentions in human PPC including object selection, action intention, and neural control of robotic limbs. Experimental results will be used to construct BMI control algorithms optimized to decode these cognitive signals. In parallel, a modular, semi-autonomous robotic prosthesis will be developed that can identify household objects and plan reach-and-grasp movements to manipulate or transport the objects. These scientific and technological efforts will be supported by continued clinical care of the tetraplegic participants. The study will explore increasingly capable iterations of the BMI system, culminating in testing of the fully developed BMI system in the participants' own home environment where they will practice activities of daily living. The resulting system will leverage deep insights in cognitive neuroscience and advanced capabilities in machine sensing and robotic control systems to substantially improve the ease of use and capability of brain-machine interfaces.","FID":28}},{"geometry":{"x":-1.35988768517E7,"y":4501269.358099997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Stanford University","Title":"MRI: Acquisition of a High-resolution X-ray Microscope for Nondestructive 2D, 3D and 4D Characterization of Microstructures in Cross-Disciplinary Research","City":"Palo Alto","State":"CA","Abstract":"X-ray computed tomography (CT) is an approach to nondestructive examination of objects based on reconstructing three-dimensional (3D) images of the external and internal features of an object from a series of two-dimensional X-ray images taken at a large number of viewing angles. Medical CT imaging is commonly used as a diagnostic tool, and similar approaches using higher X-ray intensities can allow very detailed imaging of non-living samples for a wide range of research applications across many fields of science and engineering. This Major Research Instrumentation (MRI) award supports the acquisition of a high-resolution, 3D X-ray microscope capable of producing images with three-dimensional resolution smaller than 1 micrometer (about 100 times smaller than the width of a human hair). This system will be located in the Stanford Nano Shared Facilities, a core facility providing researchers across Stanford University and from nearby institutions with state-of-the-art instruments for specimen characterization and analysis. This instrument will advance innovative research by investigators from multiple disciplines across Stanford's Schools of Earth Energy & Environmental Sciences, Engineering, Humanities & Sciences, and Medicine, as well as investigators from San Jose State University and the California Academy of Sciences, a museum, educational center and research facility in San Francisco.<br /><br />The high-resolution X-ray microscope will improve Stanford's ability to conduct leading-edge research in materials science, earth science, and life science by filling the gap in length scale (0.4 to 40 micrometers) within which no equipment currently at Stanford can generate non-destructive 3D tomography images. It will support leading-edge basic research in materials science, earth science, and life science. Researchers will use the instrument to analyze the microstructure of shale rock, which contains pores and other features at a range of sizes, enabling studies on more efficient extraction of petroleum and sequestration of anthropogenic carbon dioxide. The ability to image large samples with high resolution at a long working distance will be exploited to study silicon microparticle anodes coated with self-healing polymers for optimal design of longer-lasting batteries. The instrument will be used for high-resolution imaging of inner-ear bones and the tympanic membrane of mammals ranging from mice to humans to aid in more detailed modeling of the mechanics of hearing and development of novel devices for correcting hearing abnormalities. Researchers on improved fabrication of micro-electro-mechanical systems (MEMS) devices will use the microscope to nondestructively examine the internal structure of devices designed to minimize or eliminate fatigue (repeated loading) failure, dramatically extending the useful life of devices and sensors for a wide range of applications. The dual-energy imaging capacity will allow simultaneous collection of high-resolution images of cartilage, bone and vasculature in a single scan, providing new insights into the processes of skeletal development and healing. Researchers at the California Academy of Sciences will take advantage of the instrument's high-resolution, phase contrast imaging capabilities for detailed examination of tissue interfaces as part of studies on the anatomical and physiological effects of evolutionary miniaturization. Through these and many other projects, this instrument will become a key part of Stanford University's research infrastructure and enhance the scope and impact of research across a wide range of science and engineering disciplines.","FID":29}},{"geometry":{"x":-1.36110939041E7,"y":4561060.924000002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Berkeley","Title":"UNS:Parylene-in-Parylene (PiP) integrated photonic systems for optogenetics in microelectrocorticography (uECoG)","City":"Berkeley","State":"CA","Abstract":"PI: Maharbiz, Michel<br />Proposal: 1512794<br /><br />Implantable biophotonic devices are highly in demand for applications such as in-vivo sensing, imaging, and optogenetic neural stimulation. The researchers propose to design, fabricate, and characterize compact, flexible, and biocompatible photonic structures built entirely from Parylene. They will integrate such waveguides with switches and light sources to realize a fully reconfigurable and integrated photonic platform. <br /><br /><br />An all-Parylene photonic platform has never been published. Such an innovation would have immediate impact as Parylene is routinely used in ultra-flexible, implantable systems. Biocompatible and flexible integrated photonic structures are required that do not degrade, delaminate, or fall apart when used in chronic applications. Recent advances in flexible photonics mostly rely on transferring guided-wave devices to a flexible substrate to realize heterogeneous pseudo-flexible photonic devices. Such implementations are vulnerable to degradation and failure are only suitable for short-term diagnostic implants. The proposed research introduces a new platform for realizing compact and flexible integrated photonic devices leveraging an already well-developed biocompatible material system used for encapsulating biodevices. This program includes a well-conceived plan for outreach activities.","FID":30}},{"geometry":{"x":-1.3151759756299999E7,"y":4048618.4927999973,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"California Institute Of Technology","Title":"UNS: Fast Focus-scanning Microscopy Using Micron-thick phase Plates Based on High-index Meta-structures","City":"Pasadena","State":"CA","Abstract":"Abstract<br />Faraon<br />1512266<br /><br />Understanding how the brain works is one of the main scientific challenges of this generation. Optical techniques for neural imaging, excitation and recording play a crucial role in deconstructing the neural circuitry. Optical modulation and recording from sets of neurons is enabled by optogenetics and genetically encoded voltage sensors. To fully use this capability, the PI proposes to develop a fast and slim device capable of focusing light in a volume on the same order of magnitude as a cortical column at speeds faster than an action potential and spatial resolution smaller than a neuronal cell body. <br /><br />The enabling technology is the recent invention of dielectric meta-surfaces, structures thinner than a wavelength that allow for unprecedented control of free-space propagating light. The uniqueness of the technology stems from the capability to lithographically place the phase plates in very close proximity (tens of microns) and to actuate them at high speeds using electrostatic forces like in micro electro-mechanical devices (MEMS). If successful, this project will enable devices that could scan many neurons in a cortical column with single action potential temporal resolution, thus resulting in deconstruction of neural circuitry in that column.<br /><br />This interdisciplinary project will provide the opportunity to train a graduate student in nano-photonics and biomicroscopy. The student will simulate and fabricate the devices, will develop a complex microscope setup, and will do two-photon microscopy measurements on brain samples. In addition to graduate student education, undergraduate students will contribute to the project through the SURF program at Caltech. The PI and the graduate student will be involved in an outreach activity with the Navajo Preparatory High School, a native American high school located in Farmington, New Mexico. The activity will consist in travelling to Farmington to teach science lessons, describing the research, and setting up demonstrations for high school students visiting Caltech.","FID":31}},{"geometry":{"x":-1.36110939041E7,"y":4561060.924000002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Berkeley","Title":"Collaborative Research: Olfactory Navigation: Dynamic Computing in the Natural Environment","City":"Berkeley","State":"CA","Abstract":"This project was developed at an NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Physics of Living Systems program in the Physics Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Chemistry of Life Processes program in the Chemistry Division, and the Neural Systems Cluster in the Division of Integrative Organismal Systems. The project is a synergistic combination of laboratory experiments and computer modeling that will lead to better understanding of how animals use the sense of smell to navigate in the real world. Almost universally, from flies to mice to dogs, animals use odors to find critical resources, such as food, shelter, and mates. To date, no engineered device can replicate this function and understanding the code used by the brain will lead to many novel applications. Cracking codes, from neural codes to the Enigma code of WWII, is aided by a deep understanding of the content of messages that are being transmitted and how they will be used by their intended receivers. To crack the olfactory code, the team will focus on how odors move in landscapes, how animals extract spatial and temporal cues from odor landscapes, and how they use movement for enhancing these cues while progressing towards their targets. The proposed work encompasses physical measurement of odor plumes, behavioral measurement of animals' paths through olfactory environments, electrophysiological and optical measurement of neural activity during olfactory navigation, perturbations of the environment via virtual reality and of neuronal hardware via genetics, and multilevel mathematical modeling. The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. The project's results may lead to improved methods for the detection of explosives, new olfactory robots to replace trained animals, and new theoretically-grounded advances in robotic control. The project will inform the development of technologies that interfere with the ability of flying insects (including disease vectors and crop pests) to locate their odor target, thus opening a new door for developing 'green' technologies to solve problems that are of global economic and humanitarian importance.<br /><br />This proposal is a synergistic combination of laboratory experiments and computational modeling that will probe how animals use olfaction to navigate in their environment. Specifically, this effort seeks to solve the difficult problem of olfactory navigation through the following aims: (i) Generate and quantify standardized, naturalistic odor environments that can be used to perform empirical and theoretical tests of navigation strategies; (ii) Determine phenomenological algorithms for odor-guided navigation through behavioral experiments in diverse animal species; (iii) Determine how odor cues for navigation are encoded and used in the nervous system by recording neuronal data and simulating putative neural circuits that implement these processes; (iv) Manipulate olfactory environments and neural circuitry, to evaluate model robustness. In contrast to previous attempts to understand olfactory navigation, the present strategy emphasizes mechanisms that are biologically feasible and explores the wide range of temporal and spatial scales in which animals successfully navigate. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering (fluid mechanics, electronic olfaction, and robotics) and biology (neuroscience, ecology and evolution).","FID":32}},{"geometry":{"x":-1.31216788652E7,"y":4009766.1240999997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-San Diego","Title":"MRI: Development of a Pulsed Laser Source for Deep in Vivo Imaging, a Synergy of Physics and Brain Science","City":"La Jolla","State":"CA","Abstract":"This is a development project to construct a scanning two- and three-photon microscope for deep imaging in the brain in support of activities related to neuronal circuit analysis and neurovascular coupling. The ability to image ever deeper in the brain with optical methods is a key enabling technology in our ability to decipher neuronal anatomy and circuit function as well as neurovascular function. Optical tools, together with labels of specific brain structures, are the only means to probe the geometry and state variables of single cells, e.g., voltage and second messengers, and the dynamics of brain vasculature in a noninvasive or partially invasive manner in vivo. The current method of choice for in vivo imaging makes use of two-photon microscopy with a 100-femtosecond pulsed laser sources to observe structure and dynamics throughout the upper ~ 500 micrometers of cortex of mice. Yet there is a clear need to image throughout the full depth of cortex, 1.0 to 1.2 micrometers in mice, to determine the complete flow of information in cortical processing. There is also a need to image deeper still into hippocampus and other subcortical structures without excavated overlying tissue, as well as to determine the loci of vascular control throughout gray and while matter. The initial proposed experiments, all of which depend on the proposed instrument, address topics in fundamental brain science as well biomedicine. Fundamental issues revolve around neuronal plasticity and memory formation and include: the formation of motor memories, where the learning of a behavioral task is believed to follow from the formation of patterns of correlated neuronal output in motor cortex; the transformation of sensory signals in cortex into memory traces, such as learned fear via the amygdala and induction of depression via the habenula; the role of specific gene products, known as inducible transcription factors, in synaptic plasticity; and understanding how the prodigious adult neurogenesis in the olfactory bulb is integrated into ongoing olfactory function. More applied issues concern the role of exposure to nicotine alone in changing the basis for memory formation, as well as issues in vasodynamics, including the locus for neuronal control of its own nutriment supply through the cortical vasculature and the impact of microinfarctions on cell death within the white matter, where myelinated fibers traffic information from sensory to motor areas that span the cortical mantle. Realization of this system will permit training of graduate students and postdoctoral fellows in state of the art in vivo optical imaging. UC San Diego, along with the greater La Jolla scientific community, supports a large and highly collaborative neuroscience community with graduate students and fellows who will pursue careers at institutes throughout the county, even the world. They will be inspired to think of new experiments based on the capabilities of imaging new vistas in the brain, as well as new associated technologies, particularly in the design of optical probes of yet unmeasured variables. Lastly, the high density of potential users within this community will facilitate unanticipated refinements of deep imaging and perhaps transform the proposed development project into a turn-key design for the benefit of the global neurosciences communities. <br /><br /><br />The PI proposes to build an instrument, whose design is motivated by three threads of work, that enables two- and three-photon imaging throughout the full depth of cortex and into deeper structures. First is the use of 100-fs pulsed laser light at wavelengths of 1.3 or 1.7 micrometers, where scattering is minimized but absorption by water is still weak; second is the use of an optical amplifier to increase the energy per pulse and drive fluorescence at greater depths, and third is the use of aberration corrective optics to counteract distortion of the incident beam with increasing depth into brain tissue.","FID":33}},{"geometry":{"x":-1.35759670329E7,"y":4488809.260200001,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Santa Clara University","Title":"RUI: Conductivity, diffusion, and dispersion of photoexcited Dirac fermions in cadmium arsenide","City":"Santa Clara","State":"CA","Abstract":"Non-technical Abstract:<br />This study aims at investigating key electronic and optical excitation processes in cadmium<br />arsenide, one of the recently discovered \"Dirac semimetals\". Its electrons behave as though they are massless and exhibit very high mobilities and velocities, so the material may be considered the bulk analog of graphene. It is very stable, has a 3-D crystal structure, and can be integrated with existing electronics. It is also a starting material from which to realize a magnetic Weyl semimetal in which, unusually, the direction of the electrons' spin would be determined by the direction of their motion. This research includes the synthesis and characterization of cadmium arsenide bulk crystals and thin films, both<br />undoped and magnetically-doped, using chemical vapor deposition at reduced temperature. The research<br />measures electrons' diffusion, and uses several time-resolved probes including terahertz spectroscopy and<br />photoemission. Improved knowledge of growth methods and electronic properties of 3-D Dirac materials,<br />as provided by this research, is important in realizing the materials' technological promise. Applications<br />such as fast electronics, fast or broadband optical sensors, or actively mode-locked lasers all rely on<br />ultrafast and optical properties explored in this research. This work supports graduate and undergraduate<br />researchers (the latter at a primarily-undergraduate institution), who engage with the growth and<br />characterization of cadmium arsenide, operate laser experiments, handle cryogens, write computer code,<br />and analyze complex sets of data. Because of the scientific and industrial relevance of condensed-matter<br />physics, and the rapid growth of ultrafast technology, the students become prepared for a wide variety of<br />scientific and technical careers.<br /><br />Technical Abstract:<br />The Dirac and Weyl materials host properties including the chiral anomaly, unusual quantum<br />magneto-resistance, and predicted giant diamagnetism. Their near-lack of a Fermi surface causes<br />anomalous transport, with the scattering rate, density of states, and diffusivity strongly dependent on<br />energy; the conductivity rises linearly with frequency. The materials' restrictive phase-space suggests, in<br />analogy with graphene, that it should be possible to control their optical and transport properties on subpicosecond timescales, for instance by doping with photoexcited carriers. The investigators explore the<br />nature of these photoexcited carriers: their density and temperature; their effect on diffusivity and<br />conductivity; and their dispersion. Of particular interest is identifying the conditions under which photocarriers can exhibit the same distinctive Dirac behaviors as their host material. Selection of different pump-photon energies allow excitation of massless initial states or the higher-energy massive ones. Transient-grating spectroscopy measures photocarriers' diffusivity. Terrahertz spectroscopy measures their conductivity, indicative of scattering rate, chemical potential, and massive or massless character. Time-resolved photoemission reveals the transiently-occupied states invisible to traditional photoemission. Another part of this work improves vapor-based synthesis of cadmium arsenide crystals and films, exploring methods and effects of doping with magnetic atoms and contributing toward the effort to make a ferromagnetic Weyl semimetal.","FID":34}},{"geometry":{"x":-1.31163201096E7,"y":3986891.531800002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Irvine","Title":"Collaborative Research: Studies on Signals and Images via the Fourier Transform","City":"Irvine","State":"CA","Abstract":"The goal of this project is to develop novel statistical methods that address some of the current challenges in analyzing spatio-temporal data frequently encountered in neuroimaging. One major application of this project is to identify features in brain signals that could differentiate healthy individuals from patients with neurological or mental diseases. The second application is to identify changes that take place in a brain signal during cognitive processing (e.g., while a human learns a new motor skill or while a rat learns risks and rewards in a controlled experiment). The third application is to identify biomarkers in brain signals that could predict a stroke patient's ability to recover loss of motor functionality. The approach used to solve these problems requires a study of the oscillatory patterns in these brain signals. <br /><br />Motivated by these practical problems, statistical methods based on the discrete Fourier transform (DFT) are developed. The DFT gives an indication of the decomposition of variance in the time series. Under stationarity, the covariance of the DFT is sparse and thus a departure from sparsity is an indication of non-stationarity. Moreover, the covariance of the DFT can be utilized as a discriminator between classes of signals. Using the properties of the DFT, novel methods for (1) change-point detection in time series based on sparsity of the DFT, and (2) discrimination and classification of classes of time series based on the properties of the covariance of the DFT will be developed. The DFT will also be used to estimate the variance of functionals of the spectrum and test for serial correlation and stationarity in nonlinear time series. Validation for stationary spatial processes and non-stationary spatial processes using the two-dimensional DFT will also be developed.","FID":35}},{"geometry":{"x":-1.30660003642E7,"y":4026335.713600002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Riverside","Title":"EAGER: Biocompatibility of nanocrystalline YSZ transparent cranial implant","City":"Riverside","State":"CA","Abstract":"NON-TECHNICAL DESCRIPTION: The overall goal of this project is to develop a new generation of transparent ceramics, which may be used to replace traditional, opaque cranial implants (made from titanium and polymer-based materials). This new implant, which is referred to as a Window to the Brain (WttB) platform, allows for non-invasive optical interrogation of the brain on a recurring basis and, thus, serves as a critical enabler of emerging laser-based diagnostic (e.g., optogenetics) and therapy (e.g., photodynamic therapy) of brain pathologies and neurological disorders, such as brain cancer, stroke, traumatic brain injury, Parkinson's disease, etc. In particular, this project focuses on assessing potential problems of low temperature \"ageing\" and biofilm formation around the ceramic implant. The broad impact of this project lies in the added benefit it provides to the neuroscience community, which aims to advance understanding and improve brain disease management, thus improving quality of life and reducing healthcare costs. Furthermore, the advances made in the science and technology of novel opto-ceramic materials such as this has potential to extend to numerous other fields, including medical lasers, defense, energy, etc. This project also provides research opportunities to undergraduate and graduate students, particularly in the STEM field and for underrepresented minorities, preparing them to innovate as independent, globally-engaged engineers. <br /><br />TECHNICAL DETAILS: While traditional cranial implant materials provide the mechanical properties and acceptable biocompatibility necessary after implantation, none provide the unique combination of high fracture toughness and optical transparency that would enable physicians to diagnose and treat continuously various brain pathologies and neurological disorders. A recent feasibility study of a transparent nanocrystalline yttria-stabilized-zirconia (nc-YSZ) on an animal model showed that non-invasive optical interrogation of the brain is possible. Since aging-induced degradation has been reported in other types of YSZ implants as a result of phase change destabilization, independent assessments of a similar kind are required for transparent nc-YSZ materials. Furthermore, the optical transparency of these implants allows for laser-mediated controls to arrest and even revert excessive fouling (biofilm formation), which is another potential impediment for the use of this material for biomedical applications such as this. Therefore, the first goal of this project is to investigate if long term ageing could limit the use of transparent nc-YSZ as a medical material. The second goal is to measure the extent of biofilm formation on nc-YSZ samples and explore the use of sub-therapeutic laser irradiation approaches to remedy such a problem if it arises. The significance of this work lies in the potential of the ceramic-based WttB platform which may eventually allow advancements in the understanding of the brain, by facilitating the clinical translation of emerging optogenetic neurotechnologies. This research is timely and transformational and falls under the objectives of the BRAIN Initiative. As well, it is providing research opportunities to undergraduate and graduate students. This project is leveraging well-established programs and student organizations such as the California Alliance for Minority Participation (CAMP), UC Leadership Excellence through Advanced Degrees (UC LEADS), and the Society for Hispanic Professional Engineers (SHPE).","FID":36}},{"geometry":{"x":-1.35988768517E7,"y":4501269.358099997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Stanford University","Title":"Understanding the Links among Structure, Processing, and Electronic/Ionic Properties in Soft Mixed Conductors","City":"Palo Alto","State":"CA","Abstract":"Nontechnical Description: Mixed conductors, i.e., materials that have the ability to conduct electricity using both electrons and ions, have many potential applications. One of the most appealing areas on which these materials can have an impact is the interface between living matter, whose physiology operates via ion fluxes, and electronics, which operate by moving electrons. The goal of this research project is to provide an in-depth understanding of how the molecular structure of these materials and their processing conditions affect their ability to operate as transducers of ionic signals into electronic signals. Better knowledge of these materials could impact many areas of society, from the management of energy to human health. In addition to these broader benefits, educating students in this emerging area contributes to producing a trained workforce ready to develop materials and devices for the marketplace. Outreach efforts associated with this project involve a local high school with a large Latino population.<br /><br />Technical Description: Beyond organic electronic conductors, organic mixed conductors are a promising category of materials with potential applications in many areas, such as electrochemical cells and bioelectronics. Compared to the conventional conjugated polymers, mixed conductors have the added complexity of containing an ion-conducting phase. The interplay of the transport of the ion conducting and the electron conducting phase is at the heart of the operation of these materials. This project aims to establish the structure-property relationships in mixed conductors and to develop an in-depth understanding of how mixed conductors work. Specifically, the morphology of poly(3,4-ethylenedioxythiophene) (PEDOT)-based blends is widely tunable by changing the partner of PEDOT in the blend or by processing. The electrical characterization and modeling of the response of organic electrochemical transistors (OECT) allow the measurement of carrier mobility and the degree of entanglement of the ion conducting and electron conducting phase. Charge modulation spectroscopy is used to study the polaronic or bipolaronic nature of the carriers. Structural characterization, based on X-ray scattering and electron microscopy, is carried out to understand how morphology affects the functionality of mixed conductors. The project also plans to study new materials that integrate the ionic conduction functionality and the electronic conduction functionality in a single molecule.","FID":37}},{"geometry":{"x":-1.31630087882E7,"y":4035986.888899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Los Angeles","Title":"US-Belgium workshop: Atomic Switch Networks for Neuromorphic Reservoir Computing; Late Fall-2015/Early Spring 2016; University of Ghent-Belgium.","City":"Los Angeles","State":"CA","Abstract":"NSF CNIC proposal #1444214<br />US-Belgium Workshop: Atomic Switch Networks for Neuromorphic Reservoir Computing<br /><br />Part 1:<br />The human brain outperforms digital computers in a number of tasks such as image, motion tracking and sound recognition and decision making in complex and often noisy and error prone environments. Digital computers are by their nature poorly-suited for tasks such as autonomous control (navigation, robotics), pattern recognition (speech, vision) or prediction (weather, financial markets). A biologically inspired approach to computing, called Reservoir Computing (RC), on the other hand, has demonstrated the potential to perform complex tasks efficiently. To perform RC, a newly developed hardware platform called the Atomic Switch Network (ASN) uses nanotechnology to create billions of synthetic synapses wired up in a fashion similar to that of the neocortex in the human brain. The implementation of a functioning RC-ASN system requires the collaborative expertise from recognized world leaders in RC methods at Ghent University, Belgium and the UCLA team who have developed the ASN device. UCLA has proposed a participant-driven workshop involving invited lectures, hands-on tutorials with hardware and software and breakout discussions with the goal to accelerate realization of this new form of computers system. This workshop will provide international research opportunities to 5 US students and early career researchers, while also promoting team-building skills, student-driven collaboration, and cultural exchange. By combining concepts from nanoscience, neuroscience, and machine learning, this proposal seeks to leverage the collective expertise of all parties to advance this next-generation cognitive technology. The successful outcomes of this research will also benefit the BRAIN Initiative, which is a priority research area of the U.S.<br /><br />Part 2:<br />Atomic Switch Networks (ASN) are a unique class of biologically inspired computing architectures designed to produce a complex, dynamical system through the collective interactions of functional nanoscale materials. These self-organized devices retain the intrinsic memory capacity of their component resistive switching elements while generating a class of emergent behaviors commonly associated with biological cognition. Their capacity for non-linear transformation of input information, which is processed and stored in a distributed fashion, generates patterns of dynamic spatiotemporal activity that can be used as the basis for a computational platform. Recent efforts to model, simulate, and measure the operational dynamics of ASNs toward hardware implementation of reservoir computing (RC), a burgeoning field that investigates the computational aptitude of complex biologically inspired systems to address problems in which data is constantly changing, incomplete, or subject to errors, indicate the necessity to establish a collaboration with experts in the field of machine learning. The combined expertise of proposed workshop participants will focus on a critical assessment of how to best utilize ASN devices to overcome current operational limits on real-time signal processing in the RC paradigm such as speed, network density, and scalability. Beyond lectures and discussion sections, tutorial workshops delivered by participants from the US and EU will be utilized to disseminate/demonstrate the current status of (1) modeling/simulation of ASNs, (2) physical implementations of ASNs, and (3) physical implementations of other hardware systems (memristors, optoelectronics, etc.). Targeted outcomes include identification of specific areas for near-term collaboration and follow-on funding within existing Core programs at the NSF. This new collaboration will provide a tremendous opportunity to explore the best-case scenario resulting from the world's leading RC research with a potentially groundbreaking platform for hardware-based RC to contribute to novel approaches in real-time information processing and computation.","FID":38}},{"geometry":{"x":-1.31163201096E7,"y":3986891.531800002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of California-Irvine","Title":"NCS-FO: Collaborative Research: Understanding Individual Differences in Cognitive Performance: Joint Hierarchical Bayesian Modeling of Behavioral and Neuroimaging Data","City":"Irvine","State":"CA","Abstract":"Understanding the complex determinants of individual health and wellbeing is critical for the promotion and maintenance of a healthy world population. Wellbeing may be understood not only as the absence of physical and mental illness but also as the quality of life and optimal functioning of individuals. It is well known that individuals vary tremendously in terms of cognitive abilities and dispositions, as seen from performance on high-order cognitive tasks, decision-making preferences, and emotional competencies. However, the neural underpinnings of much of this variability are poorly understood: It is unclear how individual differences in brain structure and function across tasks and processes are linked to abilities and competencies. This project explores a mathematical and computational framework for investigating a large-sample neuroimaging and behavioral dataset in order to improve our understanding of individual differences in cognitive performance. An ultimate goal of the project is to predict individual cognitive performance in novel, real-world situations based on observed (past) behavioral and neuroimaging data and contribute to the understanding of cognitive health and wellbeing of individuals. The project will also offer many training opportunities for the next generation of scientists. <br /><br />The technical approach will build on and integrate recent advances in cognitive science, neuroscience, statistics, and machine learning. Statistical models will integrate data from both brain imaging and behavioral tests to generate predictions that otherwise may not be possible with a single source of data. The research will go beyond establishing and explaining individual differences to predicting individual cognitive performance in a variety of tasks.","FID":39}},{"geometry":{"x":-1.3151759756299999E7,"y":4048618.4927999973,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"California Institute Of Technology","Title":"Tools for Cells and Circuits","City":"Pasadena","State":"CA","Abstract":"Tracing Brain Circuits by Transneuronal Control of Transcription","FID":40}},{"geometry":{"x":-1.36110939041E7,"y":4561060.924000002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of California Berkeley","Title":"Tools for Cells and Circuits","City":"Berkeley","State":"CA","Abstract":"Novel tools for cell-specific imaging of functional connectivity and circuit operations","FID":41}},{"geometry":{"x":-1.35997815253E7,"y":4499406.3495000005,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Stanford University","Title":"Tools for Cells and Circuits","City":"Stanford","State":"CA","Abstract":"A new strategy for cell-type specific gene disruption in flies and mice","FID":42}},{"geometry":{"x":-1.35997815253E7,"y":4499406.3495000005,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Stanford University","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Stanford","State":"CA","Abstract":"Self-Motile Electrodes for Three Dimensional, Non-perturbative Recording and Stimulation","FID":43}},{"geometry":{"x":-1.3151759756299999E7,"y":4048618.4927999973,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"California Institute Of Technology","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Pasadena","State":"CA","Abstract":"Development of a scalable methodology for imaging neuropeptide release in the brain","FID":44}},{"geometry":{"x":-1.30660003642E7,"y":4026335.713600002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of California Riverside","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Riverside","State":"CA","Abstract":"Label-free 4D optical detection of neural activity","FID":45}},{"geometry":{"x":-1.35525435099E7,"y":4656945.867200002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of California At Davis","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Davis","State":"CA","Abstract":"Neuronal voltage tracers for photoacoustic imaging in the deep brain","FID":46}},{"geometry":{"x":-1.31216788652E7,"y":4009766.1240999997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of California San Diego","Title":"Large-Scale Recording-Modulation - New Technologies","City":"La Jolla","State":"CA","Abstract":"Non-degenerate multiphoton microscopy for deep brain imaging","FID":47}},{"geometry":{"x":-1.31630087882E7,"y":4035986.888899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of California Los Angeles","Title":"Large-Scale Recording-Modulation - Optimization","City":"Los Angeles","State":"CA","Abstract":"Building and sharing next generation open-source, wireless, multichannel miniaturized microscopes for imaging activity in freely behaving mice","FID":48}},{"geometry":{"x":-1.36110939041E7,"y":4561060.924000002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of California Berkeley","Title":"Short Courses","City":"Berkeley","State":"CA","Abstract":"Berkeley Course on Mining and Modeling of Neuroscience Data","FID":49}},{"geometry":{"x":-1.36276917937E7,"y":4547988.378899999,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"J. David Gladstone Institutes","Title":"Understanding Neural Circuits","City":"San Francisco","State":"CA","Abstract":"Network basis of action selection","FID":50}},{"geometry":{"x":-1.17196313071E7,"y":4868230.080200002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Colorado At Boulder","Title":"Collaborative Research: Olfactory Navigation: Dynamic Computing in the Natural Environment","City":"Boulder","State":"CO","Abstract":"This project was developed at an NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Physics of Living Systems program in the Physics Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Chemistry of Life Processes program in the Chemistry Division, and the Neural Systems Cluster in the Division of Integrative Organismal Systems. The project is a synergistic combination of laboratory experiments and computer modeling that will lead to better understanding of how animals use the sense of smell to navigate in the real world. Almost universally, from flies to mice to dogs, animals use odors to find critical resources, such as food, shelter, and mates. To date, no engineered device can replicate this function and understanding the code used by the brain will lead to many novel applications. Cracking codes, from neural codes to the Enigma code of WWII, is aided by a deep understanding of the content of messages that are being transmitted and how they will be used by their intended receivers. To crack the olfactory code, the team will focus on how odors move in landscapes, how animals extract spatial and temporal cues from odor landscapes, and how they use movement for enhancing these cues while progressing towards their targets. The proposed work encompasses physical measurement of odor plumes, behavioral measurement of animals' paths through olfactory environments, electrophysiological and optical measurement of neural activity during olfactory navigation, perturbations of the environment via virtual reality and of neuronal hardware via genetics, and multilevel mathematical modeling. The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. The project's results may lead to improved methods for the detection of explosives, new olfactory robots to replace trained animals, and new theoretically-grounded advances in robotic control. The project will inform the development of technologies that interfere with the ability of flying insects (including disease vectors and crop pests) to locate their odor target, thus opening a new door for developing 'green' technologies to solve problems that are of global economic and humanitarian importance.<br /><br />This proposal is a synergistic combination of laboratory experiments and computational modeling that will probe how animals use olfaction to navigate in their environment. Specifically, this effort seeks to solve the difficult problem of olfactory navigation through the following aims: (i) Generate and quantify standardized, naturalistic odor environments that can be used to perform empirical and theoretical tests of navigation strategies; (ii) Determine phenomenological algorithms for odor-guided navigation through behavioral experiments in diverse animal species; (iii) Determine how odor cues for navigation are encoded and used in the nervous system by recording neuronal data and simulating putative neural circuits that implement these processes; (iv) Manipulate olfactory environments and neural circuitry, to evaluate model robustness. In contrast to previous attempts to understand olfactory navigation, the present strategy emphasizes mechanisms that are biologically feasible and explores the wide range of temporal and spatial scales in which animals successfully navigate. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering (fluid mechanics, electronic olfaction, and robotics) and biology (neuroscience, ecology and evolution).","FID":51}},{"geometry":{"x":-1.17196313071E7,"y":4868230.080200002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Colorado","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Boulder","State":"CO","Abstract":"High-speed Deep Brain Imaging and Modulation with Ultrathin Minimally Invasive Probes","FID":52}},{"geometry":{"x":-1.1687689104600001E7,"y":4828233.168700002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Colorado Denver","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Denver","State":"CO","Abstract":"Optical tools for extended neural silencing","FID":53}},{"geometry":{"x":-8108352.086100001,"y":5117953.8134,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Connecticut Sch Of Med/Dnt","Title":"Tools for Cells and Circuits","City":"Farmington","State":"CT","Abstract":"Sparse, Strong and Large Area Targeting of Genetically Encoded Indicators","FID":54}},{"geometry":{"x":-8117931.3321,"y":5057822.225900002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Yale University","Title":"Understanding Neural Circuits","City":"New Haven","State":"CT","Abstract":"Multiscale Imaging of Spontaneous Activity in Cortex: Mechanisms, Development and Function","FID":55}},{"geometry":{"x":-8117931.3321,"y":5057822.225900002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Yale University","Title":"Bilateral BBSRC-NSF/BIO: Collaborative Research: ABI Development: Seamless Integration of Neuroscience Models and Tools with HPC - Easy Path to Supercomputing for Neuroscience","City":"New Haven","State":"CT","Abstract":"This project is a collaboration between the University of California San Diego and Yale University to develop a science gateway for the computational neuroscience community. A gateway such as this helps improve our understanding of how the brain works by making it easier for neuroscientists to use complex digital models of brain cells and circuits in their research. Powerful software has been developed for building and using models, and on-line resources such as Open Source Brain (OSB), ModelDB, Neuroscience Information Framework (NIF), and OpenWorm have been created to help neuroscientists find existing models, collaborate in developing new ones, and share the results of their work with others. However, models are becoming too complex for the computer hardware that is available to most neuroscientists, resulting in a critical need to use high performance computing resources (HPC). This work extends an existing Neuroscience Gateway (NSG), which was developed with support from NSF to eliminate or reduce many of the technical and administrative difficulties that previously limited neuroscientists' access to HPC (http://www.nsgportal.org/). That said, NSG users must still log in, upload models, launch simulations, and download results--a process that involves many time-consuming, error-prone steps. The expanded NSG-R will eliminate these steps by enabling on-demand, automated communication between itself and familiar working environments including resources like OSB and others mentioned above, and even with neural simulation software running on neuroscientists' own laptop and desktop computers. <br /><br />This seamless access to HPC is implemented in NSG-R by a software infrastructure that uses REpresentational State Transfer (\"REST\", the R in NSG-R). NSG-R utilizes set of web services which expose the capabilities of NSG for access via publicly available application programmer interfaces. This will allow users of neuroscience resources such as OSB, ModelDB, NIF and OpenWorm to readily access HPC from their respective websites via NSG-R. This enhances the usefulness of NSG-R, other neuroscience resources like OSB, and widely used neural simulators such as NEURON, GENESIS, PyNN, NEST, Brian and MOOSE. It also results in greater research productivity and enables wider use of large scale computational modeling by scientists and students. NSG-R will accelerate progress in brain science, and have far-reaching beneficial effects on related fields such as robotics and engineering of adaptive and learning systems. It will widen opportunities for educational and career advancement in neuroscience and engineering. Furthermore, by removing barriers that traditionally have limited access to HPC, NSG-R levels the playing field for all students and researchers regardless of their institutional affiliation. NSG-R, a free and open neuroscience gateway infrastructure, will naturally be a ready entry point for students and researchers from historically underrepresented schools and colleges. NSG-R workshops will be hosted at minority serving institutions (MSI) and opportunities for students to do internships with the NSG-R team at the University of California San Diego will be provided.","FID":56}},{"geometry":{"x":-8117931.3321,"y":5057822.225900002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Yale University","Title":"CPS: Synergy: Collaborative Research: Fault Tolerant Brain Implantable Cyber-Physical System","City":"New Haven","State":"CT","Abstract":"CPS: Synergy: Collaborative Research: Fault Tolerant Brain Implantable Cyber-Physical System<br /><br />Epilepsy is one of the most common neurological disorders, affecting between 0.4% and 1% of the world's population. While seizures can be controlled in approximately two thirds of newly diagnosed patients through the use of one or more antiepileptic drugs (AEDs), the remainder experience seizures even on multiple medications. The primary impacts of the chronic condition of epilepsy on a patient are a lower quality of life, loss of productivity, comorbidities, and increased risk of death. Epilepsy is an intermittent brain disorder, and in localization-related epilepsy, which is the most common form of epilepsy, one or a few discrete brain areas (the seizure focus or seizure foci) are believed to be responsible for seizure initiation. More recent approaches with implantable electrical stimulation seizure control devices hold value as a therapeutic option for the control of seizures. These devices, directly or indirectly, target the seizure focus and seek to control its expression. In this project we will build a multichannel brain implantable device based on emerging cyber physical system (CPS) principles. This brain implantable CPS device will incorporate key design features to make the device dependable, scalable, composable, certifiable, and interoperable. The device will operate over the life of an animal, or a patient, and continuously record brain activity and stimulate the brain when seizure related activity is detected to abort an impending seizure.<br /><br />Episodic brain disorders such as epilepsy have a considerable impact on a patient's productivity and quality of life and may be life-threatening when seizures cannot be controlled with medications. The goal of this project is to create a second generation brain-implantable sensing and stimulating device (BISSD) based on emerging CPS principles and practice. The development of a BISSD as a exemplifies several defining aspects that inform and illustrate core CPS principles. First, to meet the important challenge of regulatory approval a composable, scalable and certifiable framework that supports testing in multiple species is proposed. Second, a BISSD must be wholly integrated with the patient and fully cognizant at every instant of brain state, including dynamic changes in both the normal and abnormal expression of brain physiology and therapeutic intervention. Thus, this project seeks a tight conjunction of the cyber solution that must monitor itself and monitor and stimulate the brain using implanted, adaptable, distributed, and networked electrodes, and the physical system which in this case is the intermittently failing human brain. Third, a BISSD must function for an extensive period of time, up to the life of the patient, because each surgery to place and retrieve a BISSD carries an attendant risk. This requirement necessitates a dependable solution, which this project seeks to reliably achieve through both an understanding of the brain's foreign body response and a unique hierarchical fault-tolerant design. Fourth, an advanced salient approaches to acquire, compress, and analyze sensor signals to achieve real-time monitoring and control of seizures is employed. This project should yield a powerful, scalable CPS framework for robust fault-tolerant implantable medical devices with real-time processing that can grow with advances in sensors, sensing modalities, time-series analysis, real-time computation, control, materials, power and knowledge of underlying biology. The USA has a competitive advantage in the control of seizures in medically refractory epilepsy. In the modern era, epilepsy surgery evolved in the USA in the 1970s and spread from here to other parts of the world. Similarly, the USA enjoys a competitive advantage in BISSDs, and success in this effort will enable the USA to build on and maintain this advantage. In addition to epilepsy, advances made here can be expected to benefit the treatment of other neurological and psychiatric brain disorders.","FID":57}},{"geometry":{"x":-8117931.3321,"y":5057822.225900002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Yale University","Title":"Collaborative Research: PoLS Student Research Network","City":"New Haven","State":"CT","Abstract":"This collaborative research project, consisting of four institutions (Rice, Yale, UIUC and Princeton) aims to continue the Physics of Living Systems Student Research Network (PoLS SRN). This network has been in existence for four years and has had a dramatic impact on many graduate students, both in the US and abroad, working on the application of physical science techniques to living systems. These students now can participate in a global community that can help deal with the many complex issues involved in conducting research in such a new and inherently multidisciplinary field. These issues range from proper training, to gaining a broad perspective, to accessing technical expertise that may not be available at their home institution. In addition to the obvious broader impacts related to training of a research workforce, there are other broad impacts of this plan. Via the interaction of one of the PoLS nodes (Rice) with the biomedical community in Houston, students and faculty will be exposed to possible avenues whereby physics can contribute to human health issues. Funds to attract students from under-represented groups to network meetings will be available through the new funds administered by the newly proposed network coordinator. Also deas vetted by the PoLS SRN will be adapted to create student networks in other areas of science and engineering.<br /><br />There is by now little disagreement with the general notion that concepts and methods from physics have been a critical contributor to the increased understanding of the living world, and that its importance will be growing as the scientific world moves toward an ever more quantitative and predictive form of biology. Thus, the physics community clearly needs to train a new generation of scientists who can lead this effort, scientists who have the right mix of physics/mathematics rigor and broad knowledge of living systems from molecular scales on up. The PoLS SRN aims at creating a community of graduate students who can collectively help themselves and their mentors accelerate and enhance this training process. This is being done by a mix of in-person and virtual modes of communication, and this proposal is a plan to continue and expand these efforts; it will reach more students, improve the social networking portals, and make use of the complementary research agendas of the different network nodes to provide broad technical expertise. Doing all of this, will boost the intellectual level of the entire research field and convince the best students that the Physics of Living Systems is truly the most exciting research frontier in 21st century science.<br /><br />This project is being jointly supported by the Physics of Living Systems program in the Division of Physics, the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences, the Chemistry of Life Processes program in the Division of Chemistry, and the Cellular Dynamics and Function Program in the Division of Integrative Organismal Systems.","FID":58}},{"geometry":{"x":-8117931.3321,"y":5057822.225900002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"John B. Pierce Laboratory, Incorporated","Title":"Collaborative Research: Olfactory Navigation: Dynamic Computing in the Natural Environment","City":"New Haven","State":"CT","Abstract":"This project was developed at an NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Physics of Living Systems program in the Physics Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Chemistry of Life Processes program in the Chemistry Division, and the Neural Systems Cluster in the Division of Integrative Organismal Systems. The project is a synergistic combination of laboratory experiments and computer modeling that will lead to better understanding of how animals use the sense of smell to navigate in the real world. Almost universally, from flies to mice to dogs, animals use odors to find critical resources, such as food, shelter, and mates. To date, no engineered device can replicate this function and understanding the code used by the brain will lead to many novel applications. Cracking codes, from neural codes to the Enigma code of WWII, is aided by a deep understanding of the content of messages that are being transmitted and how they will be used by their intended receivers. To crack the olfactory code, the team will focus on how odors move in landscapes, how animals extract spatial and temporal cues from odor landscapes, and how they use movement for enhancing these cues while progressing towards their targets. The proposed work encompasses physical measurement of odor plumes, behavioral measurement of animals' paths through olfactory environments, electrophysiological and optical measurement of neural activity during olfactory navigation, perturbations of the environment via virtual reality and of neuronal hardware via genetics, and multilevel mathematical modeling. The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. The project's results may lead to improved methods for the detection of explosives, new olfactory robots to replace trained animals, and new theoretically-grounded advances in robotic control. The project will inform the development of technologies that interfere with the ability of flying insects (including disease vectors and crop pests) to locate their odor target, thus opening a new door for developing 'green' technologies to solve problems that are of global economic and humanitarian importance.<br /><br />This proposal is a synergistic combination of laboratory experiments and computational modeling that will probe how animals use olfaction to navigate in their environment. Specifically, this effort seeks to solve the difficult problem of olfactory navigation through the following aims: (i) Generate and quantify standardized, naturalistic odor environments that can be used to perform empirical and theoretical tests of navigation strategies; (ii) Determine phenomenological algorithms for odor-guided navigation through behavioral experiments in diverse animal species; (iii) Determine how odor cues for navigation are encoded and used in the nervous system by recording neuronal data and simulating putative neural circuits that implement these processes; (iv) Manipulate olfactory environments and neural circuitry, to evaluate model robustness. In contrast to previous attempts to understand olfactory navigation, the present strategy emphasizes mechanisms that are biologically feasible and explores the wide range of temporal and spatial scales in which animals successfully navigate. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering (fluid mechanics, electronic olfaction, and robotics) and biology (neuroscience, ecology and evolution).","FID":59}},{"geometry":{"x":-8090034.425899999,"y":5125617.381200001,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Trinity College","Title":"RUI: Investigations of a Novel, Bimetallic Ring System for Nucleating Beta-Sheets","City":"Hartford","State":"CT","Abstract":"With this award, the Chemical Structure, Dynamics & Mechanisms B Program of the Division of Chemistry is fudning Professor Timothy Curran of the Department of Chemistry at Trinity College to develop model systems for exploring the physical and chemical properties of beta-sheets, a common protein secondary structure wherein two protein chains are aligned parallel to each other. Formation of beta-sheets has been implicated in amyloid diseases such as Alzheimer's disease. Although there are existing model systems for beta-sheets, their use has been limited because these model systems aggregate and become insoluble, making them difficult to study. Professor Curran and his students have discovered a rigid, cyclic molecule that incorporates the metals, iron and tungsten, and they have discovered ways to append two short protein chains to this cyclic molecule. These protein chains are aligned parallel to each other. The goal of this research is to determine whether the two protein chains linked to the rigid cyclic molecule will form beta-sheets, and whether changes to the iron and tungsten atoms can prevent the problem of aggregation. If successful this work will enable other researchers to better understand the forces that drive beta-sheet formation. The project lies at the interface of organic, inorganic and biochemistry, and is therefore well suited to the education of undergraduate science students. Undergraduate co-workers, including those from groups underrepresented in sciences, and some high school students will take part in this funded project.<br /><br />Tungsten bis(alkyne)complexes are ununsual in that they are air stable. In general, the alkyne ligands rotate around the tungsten center; this is true for both acyclic and cyclic complexes. In recent work, a cyclic tungsten bis(alkyne) complex derived from a dialkynyl 1,1'-disubstitutedferrocene has been discovered and found to rather rigidly juxtapose the two alkyne ligands in solution. The rigid nature of this ring system and its ability to hold the two alkynes in close proximity will be used to explore whether peptides appended to the two alkynes will develop cross-strand hydrogen bonds and adopt beta-sheet conformations. Peptides will be appended to the alkynes via amide bonds made to either methyleneamine or methylenecarboxyl linkers. If these peptide derivatives do adopt beta-sheet conformations, then their ability to aggregate will be assessed. If aggregation is observed, oxidation of the iron atom in the ferrocene moiety will be examined to determine whether charge-charge repulsion can disrupt aggregation. The long-term goal of this work is to develop a model system for studying beta-sheets and the factors that contribute to their aggregation.","FID":60}},{"geometry":{"x":-8575158.2041,"y":4705980.529100001,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Optical Society Of America","Title":"Optics and the Brain Topical Meeting","City":"Washington","State":"DC","Abstract":"PI: Rogan, Elizabeth <br />Proposal No.: 1540895 <br /><br />The high level of technical development stimulated by the BRAIN initiatives is drawing new researchers into the field from diverse disciplines ranging from chemistry and genetics, to laser optics and neurosurgery. OSA has identified the urgent need for a forum where these researchers can come together and discuss optics in the brain at many levels. <br /><br />The researchers will participate in discussions of highly technical components of optical design and optical interactions with tissue. They will also consider the motivating factors in developing optical tools for neuroscience research across organisms, from cells and flies to rodents and humans. This meeting will provide a forum for presentation of results from projects related to the BRAIN initiative and Human Brain Project, and will stimulate new ideas and collaborations that will provide visionary direction for future projects. In addition this meeting will provide an opportunity for students, trainees and young investigators to present their work, and to hear and network with internationally-renowned invited speakers who represent the broad diversity of this burgeoning field. This meeting will serve to shape the careers of young trainees embarking on careers in which optics and the brain converge.<br />The Optics and the Brain meeting will be held at the Pinnacle Vancouver Harbourside Hotel, Vancouver, Canada April 12-15, 2015.","FID":61}},{"geometry":{"x":-8575158.2041,"y":4705980.529100001,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"George Washington University","Title":"Doctoral Dissertation Research: Brain reorganization in human evolution: Connecting structural and functional changes in the inferior parietal lobe","City":"Washington","State":"DC","Abstract":"During human evolution there have been large- and small-scale changes in underlying anatomical structures of the brain. Studying this reorganization is important for understanding the link between structure and function in the brain, and how this relationship may affect cognition and behavior. This project will look at changes in the interconnectedness and anatomy of a region of the brain related to planning and carrying out complex tool making, in humans and a number of non-human primate species. The findings will advance our scientific knowledge about how distinctive human behaviors originated and developed, ultimately contributing to our overall understanding of the origins of modern human behavior and culture. In addition, the project will support a female graduate student in the STEM sciences, provide science outreach to the public, and potentially inform future research on degenerative neurological diseases.<br /><br />The parietal region of the brain, particularly the inferior parietal lobe (IPL), experienced reorganization in the human lineage based on studies of fossil endocasts and neuroimaging scans. The IPL is particularly active in observing, planning and executing tool-use and skilled tool-making. The proposed project will integrate histological analyses of IPL microanatomy and a neuroimaging-based study of function and connectivity between the IPL and other brain regions to investigate reorganization. These methods will be applied consistently across a sample of primate species and humans to address reorganization of the IPL in human evolution. Such an integrative approach will reveal the anatomy of the human and non-human primate IPL and will show how the IPL operates within large-scale functional networks. This study will provide a detailed investigation of human-specific changes in brain evolution within a comparative and evolutionary framework, and can aid in answering questions about the origins of distinctive human behaviors, such as complex tool-making and symbolic behaviors. Thus, studying patterns of brain reorganization in the hominin lineage ultimately contributes to our overall understanding of the origins of human behavior and culture.","FID":62}},{"geometry":{"x":-9164357.7931,"y":3458848.1098000035,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"University Of Florida","Title":"ElectRx","City":"Gainsville","State":"FL","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":63}},{"geometry":{"x":-9382079.0229,"y":3560204.6805000007,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Florida State University","Title":"Parallel Encoding of Sequence and Structure in a Motor Memory Trace","City":"Tallahassee","State":"FL","Abstract":"The purpose of this project is to elucidate how serial order is coded by the brain. If you were to read this sentence aloud, you would utter a precise, ordered sequence of over 50 distinct vocal sounds in less than 10 seconds. How does the brain store the individual sounds of speech and then coordinate the production of these sounds in a meaningful order so quickly? A similar question could be asked about the pianist performing a Mozart sonata, the songs of birds, or the mating dances of insects. How the brain stores these elaborate sequences of behavior remains unknown. Using the songbird zebra finch, a model organism that learns meaningful sequences of vocal sounds like humans do, the interdisciplinary research team will test the hypothesis that the brain encodes and stores sequences of behavior through two separate mechanisms that operate in parallel: one coding mechanism for the sequence of vocal sounds and one for the vocal sounds themselves. Given the diversity of animal species that display elaborate, meaningful sequences of behavior, the findings will influence understanding across a broad array of organisms, including humans. The research plan coordinates the activity of a faculty research team from four different disciplines (Neuroanatomy, Neurophysiology, Mathematics, and Statistics) and will provide students with a unique interdisciplinary training opportunity and environment. <br /><br />Observed in nearly all animal forms (and exemplified by human speech) serial order in behavior consists of learning to organize a set of elemental gestural units into a purposeful sequence of action. Adult male zebra finches (Taeniopygia guttata) produce a highly quantifiable example of serial order in behavior (birdsong). Moreover, a premotor cortical region (HVC, proper name) is known to encode a consolidated premotor trace of song. Although consisting of similar cell types, the medial and lateral portions of HVC are hypothesized to encode the sequence (medial HVC) and syllables (lateral HVC) of song in parallel. The research team will test whether these two dimensions of song are encoded by physiological differences in 1) afferent input to medial and lateral HVC, or 2) the intrinsic network properties of medial and lateral HVC (or a combination of 1 and 2). However, parallel encoding of serial order in behavior should be hierarchical, with traces for sequence in a supervisory position over traces for elemental gestural units. The team will also test whether efferent axons emanating from medial and lateral HVC interact in a hierarchical fashion within vocal-motor cortex. Results will elucidate a network architecture for serial order in behavior and provide a computational platform to understand how learning new sequences shapes such memory architectures.","FID":64}},{"geometry":{"x":-9164174.4376,"y":3458889.3883000016,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Florida","Title":"INSPIRE_Deciphering the Genealogy of Neurons via Planetary Biodiversity Capture","City":"Gainesville","State":"FL","Abstract":"This INSPIRE project is jointly funded by the Organization Program in the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Systematics and Biodiversity Science Cluster in the Division of Environmental Biology, both in the Biological Sciences Directorate, and by the Biologial Oceanography Program in the Division of Ocean Sciences in the Geosciences Directorate, the Office of International Science and Engineering, and the Office of Integrative Activities.<br /><br />Why there is such an enormous diversity of neurons in our brains is the least understood and one of the most challenging problems in modern biology. Two factors contribute to this diversity. One is that different neurons have different functions, and the other, is that different neurons have different evolutionary histories. However, neither evolutionary history nor classification of neuronal types is established. The goal of this project is to reconstruct the genealogy of neurons and develop an unbiased classification of neurons in the majority of animal groups. This will provide a way to predict the properties of neurons and their connections. A novel approach to determine the kinds of molecules that are expressed in different neurons will be developed. To gain access to critically important organisms, the Principal Investigator will organize worldwide voyages on research vessels to collect marine animals that represent all major types of neuronal organization. Thousands of distinct neuronal populations across species will be collected and analyzed with novel computational and mathematical tools. The work will create a new field of NeuroSystematics. The team will develop and test a novel approach for distant training of undergraduate and graduate students to perform real-time analyses at any world location. The project will involve research collaborations with over 150 investigators from universities from many countries and will provide opportunities for international and underrepresented minority students to be involved in biodiversity research in remote oceanic laboratories. The project will also provide priceless resources and reference databases for several disciplines.<br /><br />The research strategy is based upon the development of a mobile version of a nano-volume capture technology designed for massive transcriptome analysis of entire nervous systems at single-cell resolution. The focus will be on animal lineages never investigated before, including phoronids, brachiopods, xenoturbellids, and rare and fragile larvae. The team will integrate phylogenomic tools and statistical geometry to characterize transcriptional divergence in cell type evolution and reconstruct neurogenic gene regulatory circuits. To incorporate the inherent statistical uncertainty in the genome, as well as natural selection within complex systems, stochastic approaches from information theory will be used to evaluate molecular diversities across dozens of classes of neuronal architectures. The genomic nature of species boundaries will be studied to reveal environmental and neurosensory limitations to the rates of speciation. Thus, deciphering the genealogy of neurons will be integrated with the functional and ecological constraints that underlie the formation of new behaviors.","FID":65}},{"geometry":{"x":-9164174.4376,"y":3458889.3883000016,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Florida","Title":"RI: Small: Efficient Statistical Computing on Riemannian Manifolds with Applications to Medical Imaging and Computer Vision","City":"Gainesville","State":"FL","Abstract":"This project develops efficient incremental algorithms are proposed for computing averages and other statistical quantities of interest from pools of data incrementally acquired. Many existing data acquisition and processing methods have reached a level of sophistication so as to be able to acquire and/or synthesize data that reside in curved spaces such as spheres, hyperboloids etc. As such data have become ubiquitous in many Science and Engineering fields, need for efficient statistical analysis of these data has emerged as an area of significant importance. Further, in this era of massive and continuous streaming data, samples of data are acquired sequentially over time. Hence, from an applications and computational efficiency perspective, the desired averaging algorithm ought to be amenable to incremental updates to accommodate the newly acquired data over time. The developed algorithms can be applied different applications, such as face recognition from videos, action recognition, trajectory averaging and clustering from videos, image and video restoration, pattern clustering and classification, etc. In the context of diagnostic medical imaging, methods developed in this project can be used to automatically discriminate between various disease classes, such as Parkinson's and Essential Tremor which are distinct types of movement disorders.<br /><br />This research investigates a general framework for recursive computation of the intrinsic mean and the principal geodesic analysis on several commonly encountered manifolds such as the manifold of symmetric positive definite matrices, the Grassmann, the Stiefel manifolds, the hypersphere, the manifold of special orthogonal matrices, and several others. The research team applies the developed recursive framework of computing statistics from manifold-valued data to several tasks namely, atlas computation from diffusion MRI in Medical Imaging, inter-class discrimination between sub-types of a neuro-degenerative disorder using diffusion MRI, face and action recognition, image and shape retrieval in Computer Vision applications.","FID":66}},{"geometry":{"x":-9164174.4376,"y":3458889.3883000016,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Florida","Title":"UNS:MEMS-based Fiber-optic Two-photon Microscopy Probe for Real Time In vivo 3D Neural Imaging in Freely Behaving Animals","City":"Gainesville","State":"FL","Abstract":"Abstract<br />PI: Xie, Huikai<br />Proposal: 1512531<br />Understanding how cellular, physiological, and anatomical changes in the brain alter behavior is one of the great challenges in basic neuroscience. An informative approach to linking brain and behavior is to continuously examine brain structure and function in actively behaving animals. The objective of this project is to develop a novel miniature two-photon microscopy (fTPM) probe and use it to image and gain insight of neural activity and anatomy in awake, freely moving animals.<br /><br />While fiber-optic two-photon microscopy (fTPM) approaches have shown promise for brain imaging in a natural state, current iterations lack efficient 3D-scanning capabilities and are not amenable for use in mice, the premier model for the mechanistic dissection of neural circuit function in the mammalian brain. The miniaturization of the probe is enabled by a unique electrothermal MEMS actuator design for both lateral and axial laser scanning. Specific tasks are (1) to develop a miniature MEMS-based fiber-optic probe with built-in full 3D scanning capability; (2) to validate the performance of the probe by performing chronic in vivo imaging of fine neural structure in cortical and deep-brain tissue in mice; and (3) to image and analyze neuronal morphology and activity, in awake, freely moving mice over time, using the miniature probe.","FID":67}},{"geometry":{"x":-8927570.1308,"y":2971217.1702000014,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Florida International University","Title":"Collaborative Research: Cortical Spreading Depression and Ionic Electrodiffusion in the Brain","City":"Miami","State":"FL","Abstract":"A major goal of this project is to gain a better understanding of cortical spreading depression. This is a disorder of the brain that is the basis of migraine aura and many other diseases of the brain including stroke and epilepsy. In this disorder the ionic environment of the brain is completely disrupted and the nerve cells turn silent, with a disturbance that spreads at speeds of two to five millimeters per minute across the brain. When this happens in the visual cortex, the brain area that processes visual information, the patient will perceive an aura, a temporary visual defect that slowly travels over the field of view. Migraine sufferers often perceive an aura (migraine aura) prior to a migraine attack. Better understanding the mechanisms of cortical spreading depression will thus help in management of migraine headache and many other pathological brain conditions. This research collaboration will train graduate students who will work on various aspects of the project. Summer schools will be held at Florida International University, which is a minority serving institution. Thus this project, accompanied with existing institutional efforts, has the potential to further the goal of increasing minority representation in the sciences. Further, this collaborative effort brings together experimentalists and theorists of diverse interests and strength, and therefore provides students with an ideal opportunity for professional growth.<br /><br />Cortical spreading depression is a massive redistribution of ionic concentrations in the brain that results in a localized temporary loss of neuronal function. This disturbance spreads through the brain at speeds of two to five millimeters per minute and is the physiological substrate of migraine aura. Although cortical spreading depression was first described over seventy years ago, the physiological mechanisms leading to the disturbance remains elusive, most likely due to the fact that it involves many biophysical processes. In this project, a comprehensive mathematical model and computational apparatus to simulate the phenomena will be constructed and validated with experimental data obtained at high spatial resolution. An important aspect of the mathematical model is that it takes into account ionic electro-diffusion, an effect that has not been properly considered in previous studies, and may also be relevant for illucidating mechanisms in many other neurophysiological settings. In particular, the effects of electro-diffusion on extracellular recordings, electroencephalography and magneto-encephalography signals will be studied, thereby improving analysis of these measurement modalities. Overall this research may have an impact in many other brain pathologies which are linked to these underlying biophysical processes.","FID":68}},{"geometry":{"x":-9394375.259,"y":3995056.5187000036,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Georgia State University Research Foundation, Inc.","Title":"Neural Mechanisms underlying Evolvability of Behavior","City":"Atlanta","State":"GA","Abstract":"This project examines fundamental questions about the features of neural circuits that affect the evolution of behavior. The species being examined are nudibranch sea slugs, which have highly accessible nervous systems that allow experiments to be conducted that are not feasible in other types of animals. The brains of nudibranchs contain only about 10,000 nerve cells (neurons), many of which can be individually identified from animal to animal within a species. Furthermore, neurons can often be identified across different species. Electrical activity can be recorded from multiple neurons to reveal neural circuitry. The connectivity of those circuits can be compared across species. This research team found that although the species have the same sets of neurons, they are wired up differently, even when the species produce similar behaviors. One goal of the project is to artificially rewire the neurons in one species to produce the neural circuit of another species and to create mathematical models that do the same. This will establish how easy it is to convert the behavior of one species into that of another. It also contributes to understanding the basic rules for generating behavior by comparing across species instead of focusing on a single species. The project engages the public by soliciting observations of nudibranch behavior from divers around the world through social media. It also provides important research opportunities to under-represented students through a research pipeline and creates resources that will be available to the scientific community to aid in identifying neurons and mapping out circuits.<br /><br />Evolvability reflects the ability to evolve. This project examines the features of neural circuits that affect the evolvability of swimming behaviors in nudibranchs. The project uses a variety of techniques to achieve its goals. First, transcriptomics is used to resolve the phylogeny of the Nudibranchia and allow phylogenic hypotheses to be tested. The brain transcriptomes further aid in the discovery of molecular markers for identified neurons, which are needed particularly in species that do not swim. Electrophysiological techniques are used to search for \"latent\" circuitry, that is, connectivity that might be present in non-swimmers and potentially activated by small changes. These changes will be applied using the dynamic clamp technique to inject artificial synaptic and membrane conductances and through ectopic expression of serotonin receptors. Finally, mathematical simulations are used to examine the consequences of different circuit architectures and their robustness for rhythmic activity.","FID":69}},{"geometry":{"x":-9394375.259,"y":3995056.5187000036,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Georgia Tech Research Corporation","Title":"EAGER: Integration of Conducting Polymers With Living Cells","City":"Atlanta","State":"GA","Abstract":"PI: Payne, Christine K. <br />Proposal Number: 1451903<br /><br />Advances in neuroscience and neuroengineering require new tools. Of specific need is the ability to interface electrical devices with the brain. The challenge is coupling hard metal surfaces to the soft environment of the brain. To address this problem, the investigators will pursue a novel direction, using soft, flexible, biocompatible conducting polymers to form nanowires within individual cells. These conducting polymer nanowires will provide a new tool for neural probes, bionic implants, regenerative medicine, and the treatment of neurological disorders.<br /><br />This research will address two specific goals; intracellular delivery of a foreign material into cells and electrochemical polymerization in a protein-rich, high salt, environment. Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) will be used as a representative conducting polymer. Aim 1 will focus on delivery of the monomer into the cell using the cell's own pinocytic machinery. Experiments will use PC-12 model neurons. Aim 2 will electrochemically polymerize the monomer to form a nanowire within the cell, establishing contacts between external electrodes and the cell. Each Aim is accompanied by extensive cytotoxicity assays to ensure the cells remain healthy during the process. In addition to the biomedical applications enabled by a hybrid conducting polymer-cell, this research will provide interdisciplinary training at the interface of engineering and life sciences for a diverse group of students at the high school, undergraduate, and graduate level.","FID":70}},{"geometry":{"x":-9394375.259,"y":3995056.5187000036,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Emory University","Title":"UNS:Optogenetic Control of Neuronal Activity With Activity-Dependent Bioluminescence","City":"Atlanta","State":"GA","Abstract":"Abstract<br /><br />Optogenetic control of neuronal activity has become a driving force in neuroscience research but its clinical application has been limited due to the fact that delivery of physical light into the brain poses a technical burden. This proposal aims to develop novel optogenetic probes that can report neuronal activity in a non-invasive manner and provide neuromodulation throughout the brain. <br /><br />This project will develop layers of spatiotemporal control over optogenetic activation by a diffusible chemical (drug) in combination with activity-dependent expression and activation. Neuromodulation will be delivered to neurons autonomously only when and where it is needed. These new reagents will offer two new versatile methods of probing neural circuitry in a noninvasive manner: optically reporting neural activity via bioluminescence and perturbing neural circuitry in a closed-loop fashion. This will be particularly important for conducting long term invivo studies and future clinical translation.","FID":71}},{"geometry":{"x":-9394375.259,"y":3995056.5187000036,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Georgia Tech Research Corporation","Title":"Spatially Patterned Nano/Microparticles to Traverse Biological Barriers","City":"Atlanta","State":"GA","Abstract":"Non-Technical: This award by the Biomaterials program in the Division of Materials Research is to create and study novel multifunctional particles which mimic bacterial processes for beneficial purposes such as drug delivery. The biomaterial is based upon a newly created form of Janus particle, which displays biological ligands on a particle in a spatially distinct manner, for example with a right and left hemisphere. Since the particle ligands are clustered and polarized, highly effective biological reactions can be harnessed by the particle to enter cells and translocate within cells. Interactions of the particles with a model of the blood brain barrier will be studied to understand the efficiency of particle delivery to the brain. This project will provide interdisciplinary training opportunities to graduate and undergraduate students on biomaterials, microtechnology, and neuroscience. The research activities will also promote the recruitment and mentoring of diverse students in cutting-edge scientific techniques through outreach in the Atlanta public high schools.<br /><br /><br />Technical: Particles that can actively traverse biological barriers, such as the blood-brain barrier, would be highly beneficial for a variety of basic science and applied purposes. Traversing biological barriers is routinely demonstrated by some pathogens. For example, the bacterium Listeria monocytogenes can asymmetrically express specific proteins to efficiently internalize into cells, escape a phagosome, and actuate within the cell cytosol via nucleated actin polymerization to escape the cell. However, designing biomaterials that can accomplish these tasks is a challenge. This study aims to create new, multifunctional particles which mimic pathogenic mechanisms to enter an epithelial cell layer and actively transport within the cell to exit on the basal side. Janus particles will be designed as a new class of multifunctional, topographically distinct particles that can autonomously transverse an epithelial barrier. These particles will be created with micropatterning technologies to produce chemically-distinct regions on the particle surface to which effector proteins are linked to mediate each step of transcytosis. The investigators hypothesize that high density of effector ligands through topographic separation will engineer particles with potent and coordinated ligand-mediated processes characteristically achieved by biological organisms. Interactions of the particles with a model of the blood brain barrier will be studied to understand the efficiency of particle delivery to and within the brain. The proposed program will help inspire graduate and undergraduate students from diverse disciplines and backgrounds to study how microfabrication technologies can harness bio-inspired effectors to create new biomimetic materials to widely impact the biosciences. Additionally the program will develop new curriculum for engineers and scientists to design multifunctional particles, which will further include the recruiting of high school students and teachers to contribute to research studies.","FID":72}},{"geometry":{"x":-9394375.259,"y":3995056.5187000036,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Georgia Tech Research Corporation","Title":"Physical Aspects of Superorganism Physiology: Construction, Circulation, and Homeostasis in Fire Ant Colonies","City":"Atlanta","State":"GA","Abstract":"Major transitions in the history of life occurred when individual biological entities came together to form interdependent groups with emergent properties that differed from the individuals. The most recent of these transitions occurred when solitary organisms joined together to form cooperative societies. This transition to sociality has been particularly remarkable because many distinct individuals are able to behave as a single organism through the coordinated actions of society members. The best examples of such \"superorganisms\" are colonies of social insects. Social insect super-organisms breathe, feed, grow, breed and modify their environments. Although each life system is important on its own, the balance at the colony level arises from coordinated action of all systems. The purpose of this research program is to discover physical principles that play important roles in super-organism physiology. Super-organism regulatory principles will be of use in systems where information and physical networks coexist, such as in pedestrian and vehicle traffic, urban and disaster landscapes, and neural and artificial networks. The proposed studies could also help explain why the biological transition to sociality has been so successful.<br /><br />The proposed studies will probe physical aspects of super-organism physiology from a \"top-down\" approach to discover emergent behavioral, biomechanical, and social features. This will be complemented by a \"bottom-up\" approach that will discover how aspects of super-organism physiology (exoskeleton, organization of circulatory system, healing mechanisms) depend on soil properties, ant morphology, grain manipulation biomechanics, and genetics. This research will be conducted using the red imported fire ant, Solenopsis invicta, as a model super-organism system. Fire ants possess highly developed social systems and work together to complete complex tasks. The goal of this research is to elucidate principles governing the functioning of the super-organism and the processes responsible for super-organism stability and success. Specifically, this program will study super-organism features that are analogous to those in single organisms including: (1) Super-organism exoskeleton construction: this research will investigate processes by which the super-organism constructs a robust exoskeleton, its nest, from cohesive granular media. Such processes will include biomechanics of excavation in different media, social interactions upon nest formation (like communication, recruitment, workload distribution) and intelligent construction methods (e.g. can ants probe grain level stresses). (2) Super-organism circulation: This research will deduce traffic optimization strategies in confined spaces. Such strategies may include separation of work tasks in space and time, localization of movement in nest space, organization of information hubs, and modification of the carrier's behavior in response to heavy traffic. (3) Super-organism nervous system: This research will discover how information is transmitted through a patterned environment through tactile interactions of individuals. The approaches used will lead to an understanding of how the superorganism nervous and circulatory systems co-exist. (4) Super-organism homeostasis of physical properties of the nest: This research will determine the response of the super-organism to perturbations arising from flooding, mechanical insults to nest networks, invasion of competitive species, and genetic variation derived from hybridization of fire ant species. The research team will leverage the representation of female group members to attract female students to study of the interface between biology and physics, which should attract students who might be discouraged by the barriers in more established fields. The research team will also explore strategies of public involvement through hands-on and DIY initiatives, collaboration with public education clubs and integration of science with the entertainment industry.","FID":73}},{"geometry":{"x":-9394375.259,"y":3995056.5187000036,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Georgia Institute Of Technology","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Atlanta","State":"GA","Abstract":"Conducting polymer nanowires for neural modulation","FID":74}},{"geometry":{"x":-9394375.259,"y":3995056.5187000036,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Emory University","Title":"Understanding Neural Circuits","City":"Atlanta","State":"GA","Abstract":"MULTISCALE ANALYSIS OF SENSORY-MOTOR CORTICAL GATING IN BEHAVING MICE","FID":75}},{"geometry":{"x":1288805.854699999,"y":6129578.685699999,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Technical University Of Munich","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Munich","State":"Bayern","Abstract":"Five-dimensional optoacoustic tomography for large-scale electrophysiology in scattering brains","FID":76}},{"geometry":{"x":-1.30244403137E7,"y":5898494.998499997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Idaho","Title":"MRI: Development of an exoskeleton for simultaneous assessment of brain, muscular, and nervous system output during functional arm and hand tasks","City":"Moscow","State":"ID","Abstract":"The development of a new instrument for simultaneous assessment of brain, muscular, and nervous system output during functional arm and hand tasks will provide unprecedented insight into the inner workings of arm and hand function, including movement intention and movement performance. The developed BiLateral Upper-extremity Exoskeleton for Simultaneous Assessment of Biomechanical and Neuromuscular Output (BLUE SABINO) would be the first of its kind with the ability to record extensive metrics from both left and right hemispheres of the brain, muscle activation patterns, and movement of both left and right arms simultaneously. Particularly evident in populations with neuromuscular impairment, there is a gap in our current knowledge between the action potentials generated by the brain and the resulting movements generated by the muscles. This Major Research Instrumentation award will address this gap by facilitating a better understanding of arm function along the full neuromuscular pathway from thought to action. BLUE SABINO will also enable further study on a variety of cutting-edge research areas from brain-computer-interfaces and virtual environment simulation to advanced control of industrial and medical robotics. <br /><br />BLUE SABINO will combine the mechanical precision and repeatability of a 28 degree-of-freedom (DOF) dual-arm exoskeleton, with existing high-end acquisition systems for collecting electroencephalographic (EEG) and electromyographic (EMG) data from the brain and neuromuscular system, as well as processing algorithms to compute general assessment metrics. The exoskeleton components will allow natural reach and grasp movements through two 14-DOF (12 active, 2 passive) wearable arms. EEG and EMG acquisition will be performed with at least 32 and 64 channels, respectively, per side. Together, the instrument will provide a groundbreaking, holistic instrument for quantitative assessment and evaluation of arm function not currently possible. Acquisition of biometric data from both left and right sides of the body will allow evaluation of unilateral and bimanual activities of daily living (ADL), as well as a means of monitoring and evaluating task performance for both healthy and impaired users. The comprehensive assessment capacity will enable transformative research across a wide spectrum of domains including: functional outcome assessment, computation and planning of targeted therapeutic approaches, advanced therapy/response correlations, novel brain-machine-body rehabilitation paradigms, and development and optimization of brain-computer interfaces (BCIs) and brain-controlled neuroprosthetics.<br /><br />This award is supported by the Engineering Directorate's Civil, Mechanical and Manufacturing Innovation (CMMI) Division along with the Chemical, Bioengineering, Environmental, and Transport Systems (CBET) Division.","FID":77}},{"geometry":{"x":-9755199.4622,"y":5143656.7711,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Chicago","Title":"Cortical Motion Coding and Gaze Control in Natural Vision","City":"Chicago","State":"IL","Abstract":"The human eye sends information to the brain at an estimated rate of approximately 10 megabits per second, roughly the speed of an ethernet connection. Processing such a large bandwidth stream of visual information on behaviorally relevant time scales requires the brain to extract and represent information from visual signals efficiently, i.e. represent the most information for the least cost in time, hardware and energy. In essence, the brain needs to compress the visual stream in much the same way that software compresses the digital representation of a movie. This coding enhancement might arise because the brain has evolved coding strategies that specifically account for the fact that because of both object and eye movements, the visual input to the eye may be correlated in space and time. As a result, the visual signals to the brain from the eye and retina may be quite predictable. One of the primary questions in current sensory-motor systems research is to what extent the brain utilizes prediction to compensate for the fact that it takes a finite amount of time to process information even though the visual scene might change in the interim. This proposal focuses on neural representation of visual motion and gaze behavior for natural motion videos and uses a novel video game environment to simplify the analysis of gaze. The project will also create a publicly available database of natural gaze recordings, analyze the statistics of natural retinal image motion, characterize the representation of naturally correlated motion stimuli in cortical neurons, and to articulate the strategy underlying gaze control. This database will benefit neuroscience, computer vision, media design, and other fields.<br /><br />The experimental approach combines cortical physiology in non-human primates with high-resolution eye movement recording in both humans and monkeys. The PI proposes to use high-resolution videos of natural moving scenes as visual stimuli while recording neural activity in motion-sensitive visual cortex. By carefully degrading the movies to make them increasingly less natural and measuring the impact on neural responses, the experiments will determine what features of the moving visual scene are represented most precisely. A second set of experiments will study the interactions between the visual scene and eye movements. The PI will develop an innovative Pong-like video game that actively engages the viewers and creates a common viewing purpose (scoring points) while simplifying the identification of the target of interest to aid analysis, thereby controlling the cognitive state of the viewer. The interdisciplinary nature of the work will provide training opportunities for undergraduate and graduate students crossing over from mathematics and physics to neurobiology, and for students with a biology background to gain skills in computational analysis.","FID":78}},{"geometry":{"x":-9761210.4935,"y":5169525.0502,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Northwestern University","Title":"CRCNS: Functional Imaging and Computational Models of Place Field Integration in Pyramidal Cell Dendrites","City":"Evanston","State":"IL","Abstract":"A fundamental question in neuroscience is to understand how different sets of neurons in a network combine or integrate their various inputs, and how both the pattern of inputs and the resulting outputs are related to behavior. Novel, even unprecedented, experimental methods have been and are being developed with which to image or record from large numbers of distributed neurons but understanding the integration step can be difficult since inputs and outputs are generally distributed over many millimeters, and it is very difficult to record from both simultaneously, especially so in a behaving animal. This project will combine experimental and computational methods to elucidate such synaptic integration in pyramidal neurons associated with mammalian spatial navigation in awake, behaving animals. The imaging data acquired from awake behaving mice will be made available to other groups and the full results will serve as a model for other research concerned with the integration of inputs in networks of neurons. The computational models will be made available on the ModelDB database and will be a resource to others working to understand other aspects of functionality in this brain region. Furthermore, the work will involve a close collaboration between experimental and computational research groups, thus giving postdoctoral fellows and graduate students cross-disciplinary research training.<br /><br />In pyramidal neurons of the hippocampus, the large dendritic tree constitutes an elaborate network of branching processes involving tens of thousands of excitatory synapses containing a variety of voltage-gated ion channels. The pattern of synaptic inputs impinging upon the dendritic arbor and the degree to which these inputs are processed by it to drive place field firing (i.e., firing correlated with spatial location) during behavior are currently unknown. The goals of the project are first to 1) develop improved computational models of dendritic place cell firing constrained by current imaging data and 2) establish new experimental techniques to image the inputs to pyramidal cells in the dendritic tree, at single spine resolution, during place field firing. Together the experiments and models will be used to 3) determine the degree to which local dendritic processing is involved in place cell firing. The proposed experiments will allow for the construction of significantly improved models of hippocampal function and the models will provide a framework within which to understand activity recorded at a local level in the dendritic tree and assemble a comprehensive picture of dendritic processing across the whole arbor.","FID":79}},{"geometry":{"x":-9823221.2146,"y":4882551.6455999985,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Illinois At Urbana-Champaign","Title":"CRCNS: Community Dynamic Imaging of Corticothalamic Projections","City":"Champaign","State":"IL","Abstract":"Massive amounts of brain imaging data open an unprecedented window into the structure and function of the brain, yet the tools to aid the understanding of the data are lagging. The main goal of this research project is to understand the dynamics of brain function, particularly in the auditory system, through global yet very high spatial and temporal resolution imaging techniques and using the state-of-the-art analytical tools developed for analysis of dynamic social networks. The interdisciplinary neuroscience and computational team, building on promising initial results, will work to adapt these tools developed for understanding human and animal behavior to the context of brain networks and the processes that happen over them. Using this innovative approach, the team will study a particular brain pathway that connects two brain regions that are critical for normal hearing. The project will not only lead to a greater understanding of brain function, but will also bring a new technique to the neuroscience toolbox which may help other investigators to study network properties of the brain. Graduate students and postdocs in computer science and neuroscience will collaborate across disciplinary boundaries, building new scientific approaches and insights.<br /><br />Top-down projections are ubiquitous in sensory systems and are poorly understood. In the current proposal, a model descending system, the auditory corticothalamic projection in the mouse, will be examined. The research team will take advantage of recent methodological developments in the study of this system and ask: What is the impact of corticothalamic projections on network interactions across populations of thalamic neurons? To answer this, a novel dynamic network analysis method known as Community Dynamic Analysis, or CommDy, will be used to analyze imaging data from a brain slice preparation that retains connectivity between the auditory cortex, auditory thalamus, and other related structures in the mouse. Both calcium imaging data and flavoprotein autofluoresence imaging data will be used for this analysis. Since this study represents the first use of CommDy in neuroscience, validation studies will be done in a simplified brain slice preparation containing bilateral motor cortices and the corpus callosum.","FID":80}},{"geometry":{"x":-9823221.2146,"y":4882551.6455999985,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Illinois At Urbana-Champaign","Title":"NRI: Human Cognition Assisted Control of Industrial Robots for Manufacturing","City":"Champaign","State":"IL","Abstract":"Advanced manufacturing, driven by industrial robots, is playing an increasing role in US economy. Robots are being used to carry out assembly, welding, material handling and fabrication. Even as such interactions are becoming more common in every phase of manufacturing, a perfect symbiotic relationship between machines and human beings is still very far away. Because of this, a majority of the robotic applications in manufacturing are currently limited to areas where a relatively low level of skill is required. This has restricted the full potential of robotics to augment human operators and improve productivity and quality of life. With recent advances in cognitive neuroscience and brain interface technologies, connecting the human cognitive thought process directly to robots and machines is possible, resulting in direct control of real world applications. By collecting the brain signals using sensors and analyzing the thought processes, many activities that take place inside the brain when humans take specific actions or think of actions can be identified and matched to known signals using fast computation. This new human-robot communication paradigm will be demonstrated by developing three manufacturing scenarios. The project will also have broad applicability in the design of robotic systems in fields outside manufacturing, including telesurgery, rehabilitation and space exploration. Results from this multidisciplinary research, which combines manufacturing, computer science and robotics, have the potential to improve the productivity of future manufacturing plants and can lead to new commercial ventures, which will help the US maintain global leadership in robotics and manufacturing, broaden participation of underrepresented groups in research, and positively impact engineering education.<br /><br />Significant future challenges in the development of a new human-robot communication system, which allows operators to perform complex high skilled tasks, will be addressed. The postulated paradigm will be explored by meeting the following intellectual challenges: (i) researching a novel methodology for communicating motion commands to a robot by imagining simple actions using a grammar called \"actemes,\" (ii) new brain-computer mode and algorithms to classify these actemes and, (iii) an intent-based system that auto-completes robotic actions based on most likely sequence of events that human operators are planning to complete. Three robotic manufacturing scenarios will be explored to demonstrate the human cognition based interactions in manufacturing environment: assembly, direct control, and quality control through object recognition. Finally, by using a non-invasive brain-computer interface a wide range of day-to-day applications of robotics will be demonstrated.","FID":81}},{"geometry":{"x":-9823221.2146,"y":4882551.6455999985,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Illinois At Urbana-Champaign","Title":"Collaborative Research: PoLS Student Research Network","City":"Champaign","State":"IL","Abstract":"This collaborative research project, consisting of four institutions (Rice, Yale, UIUC and Princeton) aims to continue the Physics of Living Systems Student Research Network (PoLS SRN). This network has been in existence for four years and has had a dramatic impact on many graduate students, both in the US and abroad, working on the application of physical science techniques to living systems. These students now can participate in a global community that can help deal with the many complex issues involved in conducting research in such a new and inherently multidisciplinary field. These issues range from proper training, to gaining a broad perspective, to accessing technical expertise that may not be available at their home institution. In addition to the obvious broader impacts related to training of a research workforce, there are other broad impacts of this plan. Via the interaction of one of the PoLS nodes (Rice) with the biomedical community in Houston, students and faculty will be exposed to possible avenues whereby physics can contribute to human health issues. Funds to attract students from under-represented groups to network meetings will be available through the new funds administered by the newly proposed network coordinator. Also deas vetted by the PoLS SRN will be adapted to create student networks in other areas of science and engineering.<br /><br />There is by now little disagreement with the general notion that concepts and methods from physics have been a critical contributor to the increased understanding of the living world, and that its importance will be growing as the scientific world moves toward an ever more quantitative and predictive form of biology. Thus, the physics community clearly needs to train a new generation of scientists who can lead this effort, scientists who have the right mix of physics/mathematics rigor and broad knowledge of living systems from molecular scales on up. The PoLS SRN aims at creating a community of graduate students who can collectively help themselves and their mentors accelerate and enhance this training process. This is being done by a mix of in-person and virtual modes of communication, and this proposal is a plan to continue and expand these efforts; it will reach more students, improve the social networking portals, and make use of the complementary research agendas of the different network nodes to provide broad technical expertise. Doing all of this, will boost the intellectual level of the entire research field and convince the best students that the Physics of Living Systems is truly the most exciting research frontier in 21st century science.<br /><br />This project is being jointly supported by the Physics of Living Systems program in the Division of Physics, the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences, the Chemistry of Life Processes program in the Division of Chemistry, and the Cellular Dynamics and Function Program in the Division of Integrative Organismal Systems.","FID":82}},{"geometry":{"x":-9823221.2146,"y":4882551.6455999985,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Illinois At Urbana-Champaign","Title":"CNIC: U.S.-Swedish Workshop on Assessment of Multimodal-Multilingual Development in Deaf and Hard-of-Hearing Children","City":"Champaign","State":"IL","Abstract":"The goal of this U.S.-Swedish workshop is to catalyze new research collaborations focused on how early visual and auditory experiences shape the linguistic and cognitive development of infants and young children, especially those born deaf or hard-of-hearing. Rather than examining only the auditory and spoken language abilities of deaf and hard-of-hearing children, the workshop's research framework will conceptualize these children as multilingual learners who experience the world both auditorily and visually. The workshop participants will address four key methodological questions: (1) what is the best neuroimaging approach for deaf and hard-of-hearing children, (2) how can we best assess communicative competence in multilingual children, (3) what are the challenges for assessment of the language environment in homes, and (4) how might effective intervention strategies be developed and validated? Swedish partners from the Department of Linguistics at Stockholm University are ideal counterparts in this endeavor because in Sweden's education system, there is extensive experience in bilingual-bicultural education for deaf and hard-of-hearing children and there are relatively high rates of cochlear implantation. Initial success at the workshop should point the way for next steps to explore the complex interplay between cochlear implantation and use of both a visual sign language and an auditory spoken language. <br /><br />For broader impact, another objective of the workshop in Stockholm is to provide a forum for U.S. doctoral students and early stage researchers to network with Swedish experts and other European academics, exposing them to new perspectives on the development of deaf and hard-of-hearing children. Deaf academics and students will be included in the workshop, alongside representatives of schools and parent groups, to maximize the potential for broad scientific impact. By shifting the framework for discussion and future research planning away from one of deficit to one of diversity, the workshop participants aim to develop innovative research proposals to address the societal problem of how to best educate deaf and hard-of-hearing children.","FID":83}},{"geometry":{"x":-9761210.4935,"y":5169525.0502,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Northwestern University","Title":"NCS-FO: Collaborative Research: Sleep's role in determining the fate of individual memories","City":"Evanston","State":"IL","Abstract":"Identifying the cognitive, computational and neural mechanisms responsible for determining why some memories survive when others fade is one of the many grand challenges facing researchers of the human mind and brain. It is widely understood that sleep plays a critical role in long-term remembering, yet what exactly happens during sleep to affect the persistence of memories remains largely unknown. This project brings together a team of researchers who will integrate multiple independent lines of work in cognitive neuroscience, cognitive psychology, and computer science in order to investigate the precise mechanisms undergone by recently-formed memory representations as a person sleeps and how these mechanisms determine which memories survive and which fade. The proposed integration of cutting-edge neural data analysis methods for EEG and neuroimaging data, basic human memory theory, and neural network modeling make possible the ability to non-invasively track individual memories in the human brain as they compete with each other and are modified during sleep. The potential advances from this work could impact education, training situations, and public health by facilitating the development of new strategies for ensuring that important memories survive after initial learning.<br /><br />Research suggests that memories compete for neural space such that reactivating one particular memory can exert \"collateral damage\" on other related memories. In other words, accessing one memory can come at the expense of later being able to access other nearby memories in the network space. The proposed studies test the hypothesis that importance shapes neural dynamics during sleep by selectively boosting memory reactivation; this boost ensures that important memories out-compete related memories during sleep, resulting in strengthening of important memories and weakening of less-important memories. To test this hypothesis, competition between memories will be elicited during sleep by playing sound cues, each of which was linked (during wake) to two different picture-location memories. Multiple interlocking approaches will track how memory competition during sleep shapes a memory's persistence versus fading. Neural network models will be used to generate predictions about how reward responses during encoding shape competitive dynamics during sleep, and how these competitive dynamics determine the eventual fates of competing memories. Predictions will be tested by using fMRI to measure neural activity associated with reward processing during encoding, EEG to measure brain activity during sleep, and pattern classifiers to decode memory activation from the sleep EEG data. Observations of competitive dynamics during sleep will then be related to later memory performance and to multivariate fMRI measures of memory change. The project has the potential to provide, for the first time, a comprehensive look \"under the hood\" at the life of a memory as it is acquired, processed during sleep, and eventually recalled. Pivotal knowledge will be gained about how variance in reward processing at encoding influences sleep replay dynamics, and about how sleep replay dynamics affect subsequent memory performance and the structure of neural representations.","FID":84}},{"geometry":{"x":-9761210.4935,"y":5169525.0502,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Northwestern University","Title":"Tools for Cells and Circuits","City":"Evanston","State":"IL","Abstract":"Sub-micrometer x-ray tomography for neuroanatomy","FID":85}},{"geometry":{"x":-9823221.2146,"y":4882551.6455999985,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Illinois Urbana-Champaign","Title":"Tools for Cells and Circuits","City":"Champaign","State":"IL","Abstract":"BRAIN Initiative: Integrated Multimodal Analysis of Cell and Circuit-Specific Processes in Hippocampal Function","FID":86}},{"geometry":{"x":-9755199.4622,"y":5143656.7711,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Rehabilitation Institute Of Chicago","Title":"Large-Scale Recording-Modulation - New Technologies","City":"Chicago","State":"IL","Abstract":"Massive scale electrical neural recordings in vivo using commercial ROIC chips","FID":87}},{"geometry":{"x":-9675182.8666,"y":4928779.103,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Purdue University","Title":"ElectRx","City":"West Lafayette","State":"IN","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":88}},{"geometry":{"x":-9633009.6374,"y":4745563.770300001,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Indiana University","Title":"RI: Medium: An Analysis of the Consequences of Cortical Structure on Computation","City":"Bloomington","State":"IN","Abstract":"Networks of cortical neurons are clearly organized into layers and columns, but relatively little is known about how these arrangements affect cortical computations. To approach this issue, a 512 micro-electrode array will be used to stimulate and record activity from hundreds of cortical neurons. With this, the inputs and outputs of a cortical network can be experimentally controlled. A recently-developed framework for understanding neural computation known as \"reservoir computing\" permits the computational power of neural networks to be quantified based on knowledge of their inputs and outputs. The 512-electrode system allows input stimulation to be localized to different cortical layers or columns. Similarly, outputs can be selected by recording from different layers or columns. Thus, the contributions of layers and columns to computations, and the types of computations they perform, can be measured and compared. The results of this research are expected to increase the understanding of how the cortex attains its remarkable computational power. In addition, the results of this work are expected to inform future designs of brain-like computing circuits. To promote scientific education and outreach, an existing software package called \"Simbrain\" will be further developed and disseminated. This package will allow students from high school level and above to understand how cortical networks transform inputs into outputs as they perform computations.<br /><br />Three specific aims will be pursued. First, the measurement of computational capacity must be based on realistic levels of random background stimulation. The high-conductance state is a well-known phenomenon in vivo resulting from constant random synaptic inputs, and is also a common feature in many (particularly reservoir computing) neural circuit models. The 512-electrode array will be used to deliver background stimulation to determine levels that will improve computational performance. Second, layer input and output locations will be studied. Using kernel quality and VC-dimension metrics, the computational power and role of each layer taken individually or as a whole will be assessed. It is possible that some layers more strongly generalize input patterns while others separate them. Thus it will be possible to dissect the computational contribution of each layer. Third, the same metrics will be applied to stimulation to one column which feeds to another. Here the computational power and role of multiple columns will be assessed, and any computational differences between columns directly stimulated by the array and columns stimulated by other columns can be observed.","FID":89}},{"geometry":{"x":-9600057.843,"y":5116046.6669000015,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Notre Dame","Title":"Statistical Dynamics of Balanced Cortical Networks","City":"Notre Dame","State":"IN","Abstract":"A quantitative understanding of the cerebral cortex is a major challenge of science in the 21st century. Mathematical and computational models are useful tools in developing this understanding since they allow scientists to test theories about which neural connectivity patterns give rise to which neural activity patterns. However, the cortex is too complex to represent every detail in a model. For example, the human cortex contains billions of neurons arranged in hundreds of interconnected subregions. Instead, mathematical studies rely on identifying fundamental organizing principles of the cortex and using them to build and study simplified models. One such principle is the widely reported balance between the activity of excitatory neurons (which promote activity in other neurons) and inhibitory neurons (which suppress activity). Most previous studies of excitatory-inhibitory balance do not account for the spatial connectivity structure of cortical neuronal networks. This project studies the implications of excitatory-inhibitory balance when the spatial structure cortical neuronal connectivity is taken into account. Prior work has shown that this combination of balance and spatial structure produces similar neural activity patterns as those observed in experimental recordings. The project will use this foundation to construct mathematical models that link anatomical features of the cortex to functional properties such as the neural coding of visual information and the neural basis of motor learning. As such, the project will contribute to the understanding of the cortex and its function. A deeper understanding of cortex can improve disease treatment, brain machine interfaces and the capabilities of intelligent machines.<br /><br />The project comprises three sub-projects that use spatially extended balanced network models to provide new insights into the following three features of cortical networks: (1) Correlations between the activity of neurons. Correlated neural activity plays a role in neural coding and disease. Previous balanced network models produce small correlations in contrast to larger correlations observed in many cortical recordings. This project explores how spatial network structure introduces new network states with larger correlations. (2) Intrinsic dynamics. Previous balanced network models produce simple macroscopic dynamics, but the computations required to learn new motor sequences rely on more complicated network dynamics. This project explores the rich dynamics exhibited by spatially extended balanced networks and their ability to support motor learning. (3) Sensory coding. This project explores the impact of balance on sensory coding in a model of the primary visual cortex that accounts for the intricate spatial structure of orientation tuning maps. The mathematical techniques developed in this project represent novel approaches to studying spatially extended neuronal networks, which typically involve nonlinear integral equations. In the proposed work, excitation-inhibition balance is exploited to show that these equations become linear at large system size, facilitating the analysis of networks with realistic neuron models and connectivity structure. The novel mathematical approaches contribute to the general study of complex systems and dynamics on large networks.","FID":90}},{"geometry":{"x":-9730796.0411,"y":4788714.569899999,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Indiana State University","Title":"MRI: Acquisition of a Liquid Chromatograph-Mass Spectrometer to Support Undergraduate Research","City":"Terre Haute","State":"IN","Abstract":"With this award from the Major Research Instrumentation (MRI) and Chemistry Research Instrumentation and Facilities (CRIF) programs, Indiana State University will acquire an ultra-high pressure liquid chromatograph interfaced with a linear ion trap mass spectrometer capable of data-dependent tandem mass spectrometery. The system will be used to separate and analyze the composition of mixtures of substances obtained from various sources including samples obtained from chemical reactions, energy-related research and batteries used for energy storage. In this instrument the liquid samples are allowed to pass through columns filled with substances that interact to various degrees with the sample components and thus the components move at different speeds through the columns. This process allows separation of the components. These species are then analyzed using the mass spectrometer in which the components are ionized and their masses are determined by measuring the mass to charge ratio (m/z) of the ions. This is a widely used analytical tool to determine the composition of a mixture or material. Students will be trained to use this modern instrumentation while working in their research, preparing them for their later careers. The instrument will enable new undergraduate laboratory and research experiences. It will also be used in the Summer Undergraduate Research Experiences (SURE) program which engages a large number of undergraduate students across the sciences. Besides serving multiple departments at ISU, it will support users from neighboring institutions including St. Mary-of-the-Woods College.<br /><br />The instrument will be used in research especially in areas such as (a) isolating, synthesizing and structural elucidating neuroactive natural products; (b) analyzing multimodal signaling systems in sceloporus lizards; (c) correlating analysis of organics and volatile trace elements in carbonaceous chondrites; (d) carrying out cleavage analysis of plant and fungal tyrosinases; and (e) carrying out applications of gas-phase ion molecule chemistry.","FID":91}},{"geometry":{"x":-9675182.8666,"y":4928779.103,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Purdue University","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"West Lafayette","State":"IN","Abstract":"Optical Tools to Study Neuropeptide Signaling","FID":92}},{"geometry":{"x":-9675182.8666,"y":4928779.103,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Purdue University","Title":"Large-Scale Recording-Modulation - Optimization","City":"West Lafayette","State":"IN","Abstract":"High resolution deep tissue calcium imaging with large field of view wavefront correction","FID":93}},{"geometry":{"x":-7915484.3913,"y":5216082.6928,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Charles Stark Draper Laboratory Inc.","Title":"HAPTIX","City":"Cambridge","State":"MA","Abstract":"Develop neural interfaces to improve fine motor control and restore sense of touch and proprioception for prosthetics users.","FID":94}},{"geometry":{"x":-7929417.255100001,"y":5228624.781000003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Mit Lincoln Laboratory","Title":"ElectRx","City":"Lexington","State":"MA","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":95}},{"geometry":{"x":-7915484.3913,"y":5216082.6928,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Massachusetts Institute Of Technology","Title":"ElectRx","City":"Cambridge","State":"MA","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":96}},{"geometry":{"x":-7915484.3913,"y":5216082.6928,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Harvard University","Title":"Ideas Lab Collaborative Research: Using Natural Odor Stimuli to Crack the Olfactory Code","City":"Cambridge","State":"MA","Abstract":"This project was developed during a NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Chemistry of Life Processes program in the Chemistry Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Physics of Living Systems program in the Physics Division, the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Division of Biological Infrastructure, and the Division of Emerging Frontiers. The sense of smell is essential for maintaining quality of life in humans, and its decline can be an important harbinger of neurodegenerative disease. Moreover, since nearly all animals aside from primates rely on olfaction for most survival functions, understanding chemical sensing has immense practical value, for example, in the control of agricultural pests or in training animals to detect odors relevant for bomb, drug and cancer detection. In spite of its importance, the understanding of olfaction lags far behind the other senses, which is in part due to the lack of understanding of the physical space of odors. The understanding of the neural bases of vision and audition were greatly advanced by investigations of the physical dimensions of visual and auditory stimuli. It is therefore likely that a similar in-depth investigation of odor space - how natural odors occur and the backgrounds against which they must be detected - will reveal a new depth of richness of neural representations of odors in the brain. Insects such as the fruit fly and honey bee are excellent models for this research because of the accessibility of their central nervous systems, because of their ease of use under controlled laboratory conditions, and because of the functional similarity of how odors are processed in insect and mammalian brains. This research will characterize how odor flowers and fruits with respect to behavioral value for honey bees (food) and fruit flies (food and egg laying sites). Further monitoring of neural activity in early and later stage processing in the brain, when combined with computational modeling, will reveal significantly richer neural representations than have heretofore been described. This new understanding stands to have an impact on understanding how healthy brains encode sensations and memories of odors and how brains fail under disease conditions. It will also have an impact on understanding how the sense of smell may be built into engineered devices. Finally, both insects are also of economic importance to agriculture for crop pollination (honey bees) and damage to fruit (fruit flies). The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. <br /><br />This research will quantitatively characterize the real-world statistics of multi-component natural odor scenes and investigate how they drive behavior and processing in several brain regions. The focus will be on honey bee as well as fruit fly adults and larva as models, where it will be possible to characterize a library of ethologically relevant natural odors associated with a diversity of behavioral outputs. The work will begin by quantitatively characterizing the detailed statistical properties of natural odor scenes in defined ethological contexts. This will build on the rich literature on identified natural odors in insects and mammals. Naturally occurring plant and fruit odor samples from the natural environments of each insect will be collected and chemically analyzed. Nonlinear dimensionality reduction techniques and approaches based on sparse coding will determine the dimensions of odor space that are most salient for behavioral decisions. Such a quantitative deconstruction of the sensory input would be unprecedented in olfactory neuroscience, and should allow the PIs to effectively and comprehensively drive olfactory circuits for the first time. The hypothesis is that the stimulus dimensions that are most behaviorally relevant to the animal will be most efficiently extracted by the olfactory system. Synthetic odor blends will be specially constructed to vary along relevant sensory dimensions, to probe neural codes and adaptive behaviors in the olfactory system. As in research on the visual system, analysis of such evoked neural responses using statistical methods that take into account natural odor statistics will reveal novel olfactory computations and behaviors that have been previously inaccessible. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering and biology.","FID":97}},{"geometry":{"x":-7929879.489800001,"y":5217536.326099999,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Brandeis University","Title":"INSPIRE: Memory Storage by Variable-size Stable Structures","City":"Waltham","State":"MA","Abstract":"The mechanism of memory is one the major mysteries of biology. Recent work suggests that as a result of learning synapses grow and that the size of the synapse is what stores the components of memories. The aim of the proposed work is to visualize directly this growth process in brain tissue using a newly developed super-resolution microscope, and to understand why such structures have stable size once learning has occurred. Instability would result is loss of memory, so evolution is thought to have favored ways of maximizing stability. To gain insight into the mechanism of stability, physical and computational model systems will be used. If the principles that underlie stability in the face of variable size can be understood, the outcome of this work could open the door to a new era in nanotechnology in which these principles could be utilized, leading potentially to novel solutions to problems in self-assembly. Additional contributions of this project include the organization and instruction of a course in the scientific programming language, MATLAB, in an enrichment course for students from groups under-represented in science and technology, and the opportunity for US trainees to participate in an international collaboration. <br /><br />This proposal focuses on supramolecular structures that do not have fixed size but can exist in multiple different sizes, all of which are stable. Thus, if a stimulus causes the transition from one stable state to another, the structure has information storage capability (memory). The investigators termed this type of structure variable-size stable structures (VSSS). Interest in VSSS arises from two seemingly unrelated fields: neuroscience and the physics of nanostructures. The molecular basis of memory is one the most fundamental unsolved problems in neuroscience. Evidence strongly suggests that synapses grow to encode memory. Thus, memory storage in the brain appears to be a structural problem, and efforts need to be made to understand the structural principles that make memory storage possible. The project integrates cutting-edge optical microscopy with theoretical modeling. Utilizing a newly-available super-resolution microscope, the investigators will make the first effort to observe synaptic growth during synaptic plasticity in real time. The goal of the theoretical efforts is to develop a physical theory of VSSS and evaluate different models, including ones that have emerged from the study of synapses. Questions to be addressed include: (i) The importance of cooperative interactions among multiple components to generating stable yet kinetically accessible and reconfigurable assemblages. (ii) Design principles that lead to self-terminating assembly, such as growth by finite-size modules. (iii) Mechanisms by which nonequilibrium energy consumption changes the limits of VSSS. An ultimate goal is a generalized theory for nonequilibrium self-assembly capable of describing VSSS. <br /><br />This project is jointly funded by the Neural Systems Cluster in the Division of Integrative Organismal Systems and by the Physics of Living Systems Program in the Physics Division.","FID":98}},{"geometry":{"x":-7915484.3913,"y":5216082.6928,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Massachusetts Institute Of Technology","Title":"NCS-FO: Algorithmically explicit neural representation of visual memorability","City":"Cambridge","State":"MA","Abstract":"As Lewis Carroll famously wrote in Alice in Wonderland - It's a poor sort of memory that only works backwards-. On this side of the mirror, we cannot remember visual events before they happen; however, our work will help predict what people remember, as they see an image or an event. Our team of investigators in cognitive science, human neuroscience and computer vision bring the synergetic expertise to determine how visual memories are encoded in the human brain at milliseconds and millimeters-resolution. Cognitive-level algorithms of memory would be a game changer for society, ranging from accurate diagnostic tools to human-computer interfaces that will foresee the needs of humans and compensate when cognition fails. <br /><br /><br />The project capitalizes on the spatiotemporal dynamics of encoding memories while providing a computational framework for determining the representations formed from perception to memory along the scale of the whole human brain. A fundamental function of cognition is the encoding of information, a dynamic and complex process underlying much of our successful interaction with the external environment. Here, we propose to combine three technologies to predict what makes an image memorable or forgettable: neuro-imaging technologies recording where encoding happens in the human brain (spatial scale), when it happens (temporal scale), and what types of computation are performed at the different stages of storage (computational scale). Characterizing the spatiotemporal dynamics of visual memorability, and determining the type of computation and representation a successful memorability system performs is a crucial endeavor for both basic and applied sciences.","FID":99}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Massachusetts General Hospital","Title":"NCS-FO: Nanomagnetic Stimulation Capability for Neural Investigation and Control","City":"Boston","State":"MA","Abstract":"ECCS- Prop. No. 1533598<br /><br />PI: Gong, Yiyang <br />Institute: Duke University<br />Title: NCS-FO: Real-time optical readout and control of population neural activity with cellular resolution<br />Objective: <br />This project will develop a mechanism for simultaneously controlling and reading out neural activity when being activated by optogenetic techniques; this capability will surpass a previous limitation in neural studies. The proposal is separated into three aims: 1) develop calcium sensors and optogenetic channels active on different wavelength ranges to allow simultaneous readout and control, 2) develop a dual-beam two photon microscope, and 3) develop imaging software that can process neural activity in real-time. <br /><br />Nontechnical abstract<br />Understanding neural function requires examining specific subsets of the vast numbers of neurons in the brain. Recently developed optogenetics tools, such as optogenetic stimulation and calcium imaging, have partially fulfilled the need to target these specific sets of neurons and study their function. These techniques deliver engineered genes to targeted neural populations, and use light to manipulate or measure neural activity. Current optogenetic tools lack the spatiotemporal resolution to causally study many individual neurons in parallel on fast time scales; they only make broad conclusions either on near-millimeter sized brain regions, or over the timescale of many action potentials. We propose to integrate the design and implementation of optical and genetic tools to greatly refine the scale of investigating neural activity. Specifically, we will create two optically independent channels: one channel for fast, spatially precise optical patterning to control individual neurons; and one channel for independent recording of neural activity from individual neurons. We will then integrate these two channels by creating software that instantaneously patterns optical excitation based on the optical recording. Integrative design and engineering of this expansive set of tools will enable neuroscientists to quickly manipulate and control large populations of single neurons, a capability that does not exist presently. Our technology will allow the community to directly explore how neural activity patterns of many individual neurons in one brain region drive downstream neural activity. This novel probing of functional connectivity is exactly the type of study needed to better understand the coordination of neural activity in healthy and diseased brains. Beyond the specific application of neuroscience, training students within our multidisciplinary setting will create the next generation of scientists capable of tackling the broad set of technical challenges facing society today. <br /><br /><br />Technical Abstract<br />Optical imaging of brain activity has steadily developed into a staple technique within neuroscience labs over the past decade. In combination with genetically encoded sensors of neural activity, optical methods enable genetic targeting and chronic, simultaneous imaging of many individual neurons. One significant weakness of existing optical techniques when compared to electrophysiology is the inability to simultaneously measure and control the activity of a neuron in real time. We propose to address this shortcoming by developing an optical imaging system and data processing software suite that will enable real-time optical readout of neural activity and real-time neural feedback via optical excitation, all with cellular level specificity and in parallel over a large population of neurons. This new ability to optically record and manipulate many genetically or functionally specified neurons individually will augment current studies using bulk neural activation or inhibition; the fine scale perturbations of neurons will tease apart the details of neural circuits. Specifically, we will engineer a set of optogenetic actuators, fluorescent sensors, and microscopy tools that will enable optical readout and control of neurons in different wavelength channels. We will also develop fast image processing algorithms that quickly convert images to neural activity of individual neurons, thereby enabling real-time control of neural activity based on the optical readout. Recently, improvements to these tools occurred independently. Our proposal will address the integrated development of the tool set, and effectively employ trade-offs between the individual components. For example, simultaneous engineering of the protein sensor, imaging processing software, and optical imaging hardware will optimize the readout fidelity. Similarly, joint design of the genetic tools? spectral separation and the optical spatiotemporal resolution will extend optical control precision. Integration of these developments to examine neural function at the cellular level is unprecedented: successful advancement of this research will enable novel examination of the brain and help guide targeted biomedical therapies.","FID":100}},{"geometry":{"x":-7915790.733200001,"y":5224074.4076000005,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Tufts University","Title":"Collaborative Research: EAGER: Biomanufacturing: Bioengineering of 3-dimensional brain surrogate tissue models","City":"Medford","State":"MA","Abstract":"PI: Demirci, Utkan<br />Proposal Number: 1547791<br /><br />PI: Kaplan, David L. <br />Proposal Number: 1547806 <br /><br />The coordinated function in the brain of billions of neurons in dense and entangled networks can be seen as the epicenter of our unique higher consciousness, as well as of our vulnerability to debilitating diseases, such as schizophrenia, autism and Alzheimer's. The investigators propose a unique approach of sound waves and silk protein biomaterials, to recreate the complex three-dimensional brain network structures in a small dish, and use them to investigate their response to a laboratory model of brain concussion damage. With these studies, the investigators aspire to demonstrate how these constructs may help scientists better understand the workings of the brain in healthy and diseased states.<br /><br />The complexity of the brain poses a large roadblock for scientists to examine molecular, cellular and circuit level behavior of brain physiology. Novel approaches and technologies are needed that complement and advance the existing in vivo, ex vivo and in vitro approaches. The goal of the proposed research is to develop a new flexible bioprinting platform for the in vitro fabrication of 3-dimensional (3D) neural tissue constructs that faithfully mimic the biological complexity, development, architecture and function of 3D circuits present in the brain. The key innovations include the strategy of acoustic biopatterning and silk protein scaffolds for encapsulating neurons in long-lived, 3D multilayered architectures. To prototype and validate the construct, the investigators propose in the first aim to create 6-layer cortical circuits built of primary neurons. In the second aim, they will examine the physiology of the 3D circuit tissues using a comprehensive neuro-technological tool-box. Electrophysiology, fluorescence imaging, genomics and proteomics approaches will be employed to evaluate functional and structural milestones of the developing in vitro 3-D neural circuits, including a brain damage disease model. This radically different approach for investigating brain physiology and pathophysiology has the potential to provide new tools for neuroscience, the utility of which extends to other fields because of the general applicability of the proposed advanced biomanufacturing approaches. The broader impact of this proposal includes the participation of high school, undergraduate and graduate level scientists in research at the intersection of neuroscience, tissue engineering and biomanufacturing, thus presenting a useful platform for the training of interdisciplinary scientists.","FID":101}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Northeastern University","Title":"NCS-FO: Nanomagnetic Stimulation Capability for Neural Investigation and Control","City":"Boston","State":"MA","Abstract":"ECCS- Prop. No. 1533598 <br /><br />PI: Gong, Yiyang <br />Institute: Duke University <br />Title: NCS-FO: Real-time optical readout and control of population neural activity with cellular resolution <br />Objective: <br />This project will develop a mechanism for simultaneously controlling and reading out neural activity when being activated by optogenetic techniques; this capability will surpass a previous limitation in neural studies. The proposal is separated into three aims: 1) develop calcium sensors and optogenetic channels active on different wavelength ranges to allow simultaneous readout and control, 2) develop a dual-beam two photon microscope, and 3) develop imaging software that can process neural activity in real-time. <br /><br />Nontechnical abstract <br />Understanding neural function requires examining specific subsets of the vast numbers of neurons in the brain. Recently developed optogenetics tools, such as optogenetic stimulation and calcium imaging, have partially fulfilled the need to target these specific sets of neurons and study their function. These techniques deliver engineered genes to targeted neural populations, and use light to manipulate or measure neural activity. Current optogenetic tools lack the spatiotemporal resolution to causally study many individual neurons in parallel on fast time scales; they only make broad conclusions either on near-millimeter sized brain regions, or over the timescale of many action potentials. We propose to integrate the design and implementation of optical and genetic tools to greatly refine the scale of investigating neural activity. Specifically, we will create two optically independent channels: one channel for fast, spatially precise optical patterning to control individual neurons; and one channel for independent recording of neural activity from individual neurons. We will then integrate these two channels by creating software that instantaneously patterns optical excitation based on the optical recording. Integrative design and engineering of this expansive set of tools will enable neuroscientists to quickly manipulate and control large populations of single neurons, a capability that does not exist presently. Our technology will allow the community to directly explore how neural activity patterns of many individual neurons in one brain region drive downstream neural activity. This novel probing of functional connectivity is exactly the type of study needed to better understand the coordination of neural activity in healthy and diseased brains. Beyond the specific application of neuroscience, training students within our multidisciplinary setting will create the next generation of scientists capable of tackling the broad set of technical challenges facing society today. <br /><br /><br />Technical Abstract <br />Optical imaging of brain activity has steadily developed into a staple technique within neuroscience labs over the past decade. In combination with genetically encoded sensors of neural activity, optical methods enable genetic targeting and chronic, simultaneous imaging of many individual neurons. One significant weakness of existing optical techniques when compared to electrophysiology is the inability to simultaneously measure and control the activity of a neuron in real time. We propose to address this shortcoming by developing an optical imaging system and data processing software suite that will enable real-time optical readout of neural activity and real-time neural feedback via optical excitation, all with cellular level specificity and in parallel over a large population of neurons. This new ability to optically record and manipulate many genetically or functionally specified neurons individually will augment current studies using bulk neural activation or inhibition; the fine scale perturbations of neurons will tease apart the details of neural circuits. Specifically, we will engineer a set of optogenetic actuators, fluorescent sensors, and microscopy tools that will enable optical readout and control of neurons in different wavelength channels. We will also develop fast image processing algorithms that quickly convert images to neural activity of individual neurons, thereby enabling real-time control of neural activity based on the optical readout. Recently, improvements to these tools occurred independently. Our proposal will address the integrated development of the tool set, and effectively employ trade-offs between the individual components. For example, simultaneous engineering of the protein sensor, imaging processing software, and optical imaging hardware will optimize the readout fidelity. Similarly, joint design of the genetic tools? spectral separation and the optical spatiotemporal resolution will extend optical control precision. Integration of these developments to examine neural function at the cellular level is unprecedented: successful advancement of this research will enable novel examination of the brain and help guide targeted biomedical therapies.","FID":102}},{"geometry":{"x":-8074358.531300001,"y":5216682.205700003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Massachusetts Amherst","Title":"NSC-FO: Collaborative Research: Individual variability in human brain connectivity, modeled using multi-scale dynamics under energy constraints","City":"Amherst","State":"MA","Abstract":"Recent years have witnessed an explosion of interest in human brain connectivity and its relationship to brain-based disease. Functional connectivity analyses in neuroimaging have taken three general forms: cross-correlations, weighting of directed connections, and graph-theoretic approaches. Graph-theoretic measures, in particular, provide valuable insights into network features at the time of imaging. Yet, they cannot identify how the brain came to have those features, nor can they inform estimation of future network evolution. Neurological and psychiatric illnesses tend to have degenerative or oscillatory time-courses that range over decades; thus, network evolution will be critical to understanding why two individuals with the same diagnosis show markedly distinct developmental onsets and prognoses. <br /><br />At the most fundamental level, clinical neuroscience currently lacks the tools for probing how biological constraints imposed upon synapses impact functional connectivity patterns. These constraints include, among others: limited energy resources as per the aggregate energy conversion rate of a finite number of mitochondria, the need to balance excitatory and inhibitory neurotransmitters in order to maintain homeostasis, and neural repair mechanisms (e.g., inflammation, MMP-9). Our long-range goal is to develop these tools, focusing first upon energy constraints across synaptic-hemodynamic scales, for three strategic reasons. 1) Glycemic load is implicated in many neurological diseases, including epilepsy, brain cancer, and dementia. 2) Energy utilization is easy to manipulate experimentally through diet, and to quantify via CO-2 monitoring, with protocols that permit translation to/from animal models for multi-scale modeling. 3) Recent findings link neural connectivity to metabolic expenditure. In the short-term, we focus upon establishing feasibility for three critical principles in preparation for the proposed work. First, we will conduct a pilot neuroimaging study (36 scans; N=12, under three conditions) to establish that our proposed experimental manipulation of energy supply and demand provokes reorganization of brain networks. Second, we aim to bridge scales: to demonstrate how agent-based simulations of point-neurons can incorporate network structure imposed at the level of human neuroimaging, and evolve as a function of changing inputs (energy supply, demand). Third, we propose to develop/adapt methods required to mathematically characterize dynamic networks for both fMRI data and simulations. This fundamental work will position us to conduct future research on modeling of metabolic processes as a function of synapses, glia, and mitochondria, and to use these simulations to predict individual variability of fMRI results as a function of neural energy consumption.","FID":103}},{"geometry":{"x":-7926737.8772,"y":5211828.916100003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Neurofieldz Inc.","Title":"SBIR Phase I: Novel Electric Field Encephalography Sensors for Neuromonitoring","City":"Newton","State":"MA","Abstract":"The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is development of a new neuroelectric sensor (NeuroDot) for brain monitoring that will measure electric fields generated by brain activity using a new technique termed Electric field Encephalography (EFEG) with best-in-class sensitivity. The EFEG brain monitoring technique is a new modality that has several advantages over the current modalities, electroencephalography EEG (which measures the electric potential on the scalp) and magnetoencephalography MEG (which measures the magnetic field). The NeuroDot brain sensors are quickly mountable and demountable and enable 24/7 neuromonitoring with wireless connectivity to smartphones and wearable technologies like smartwatches. The NeuroDot sensors provide neurological data analyzed with subsequent software post-processing to provide information on the activity of the brain for analysis of the mental health state. Some of the immediate areas of impact of the EFEG technology based NeuroDot sensors include functional brain imaging at high temporal and spatial resolution to enable localization of epileptic seizures, and understanding of pattern recognition and cognition by the brain. The signals from these sensors will provide insights into mental conditions related to aging, sleep, epilepsy and neurological disorders. The high performance NeuroDot sensors will also be usable for human-machine and brain-computer interfaces.<br /><br />This proposed project will improve and optimize the current NeuroDot prototype to create marketable products that meet specifications for real-time neuromonitoring. This project will achieve its aims through the following Goals. Goal 1: Optimize the wireless NeuroDot sensor to meet metrics and milestones for real-time neuromonitoring. Goal 2: Perform Usability Testing and Sensor Performance Benchmarking through studies on human subjects. The project will develop breakthrough nanodendritic electrodes and wireless technologies for the NeuroDot sensor for long-term low noise EFEG recordings in a compact (","FID":104}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Trustees Of Boston University","Title":"UNS:Fluorescence light-field imaging with a lensless flexible fiber bundle","City":"Boston","State":"MA","Abstract":"PI: Mertz, Jerome<br />Proposal: 1508988<br /><br />The objective of this proposal is to build an ultraminiaturized imaging device that can be used to image at arbitrary depths within tissue, and to reach confined regions in samples that are difficult to access.<br /><br />A key feature of the device is that it will be able to focus to variable depths, even though it is lensless in design and contains no moving parts. The device can be used with any type of luminous object, such as fluorescence, bioluminescence or even white-light illuminated scenes. The device is based on an invention the PI recently patented that enables high-throughput imaging through a single optical fiber. This uses the principle of a spread-spectrum encoder (SSE), wherein light-ray directions entering a fiber are converted into unique, broadband, fingerprint spectral codes that then propagate through the fiber to be detected and decoded at the other end. Because image information (i.e. ray directions) is converted into spectral information, this information becomes insensitive to fiber bending or motion, so that the technique can readily be used for microendoscopy applications.","FID":105}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Massachusetts General Hospital","Title":"Collaborative Research: Unraveling Cerebral Connectivity with Diffusion MRI, Microscopy and Statistical Physics","City":"Boston","State":"MA","Abstract":"A better understanding of the relationship between brain structure and function is an integral component of the on-going efforts aimed at developing a better understanding of the human mind. Fundamental research is required to accelerate the development of new technologies for neuroscience and near engineering in order to address important societal needs with respect to the development of new ways to treat, prevent, and cure brain disorders. In this larger context, this collaborative project will extend methods of statistical physics to bridge from microscopic neurobiological observations of neurons, axons and dendrites to the mesoscopic images of brain organization seen in diffusion MRI images of the entire primate brain. A particular focus will be to address the question of how the processes of the brain might exploit this special architecture for the representation and processing of information, and in particular, how this regular structure might support time-coding and synchronization of information across the brain.<br /><br />Joining a physics laboratory, a neurobiology laboratory, and an MRI laboratory, this team will investigates the hypothesis that brain connectivity is geometrically organized, with connectivity generally aligned with the axes of a curved, but essentially orthogonal coordinate system or 3D grid. The idea that the brain of all species with bilateral symmetry is based on an orthogonal plan is not new. It has been recognized in embryology and evolutionary biology for nearly 100 years and more recently has been validated in detail in studies of gene expression. Preliminary studies have suggested that this orthogonal motif pervades the structure of the brain, and particularly connectivity, from macroscopic down to a cellular level. In this interdisciplinary project, the investigators will quantify this phenomenon by looking at structural data from both diffusion MRI and advanced methods of 3D light microscopy and then apply the ideas and tools of condensed matter physics to characterize the structure and circuits of the brain as organized matter. As a first example, having observed 3 orthogonal fiber directions at each point in the brain that vary smoothly, it is natural to model this as a liquid crystal with a deformation energy and temperature. Then, one can investigate its scaling in the brain, and transitions such as those from white matter to gray matter. Functionally, we hypothesize that this rectilinear grid, may provide a new mechanism for neural activity to be temporally correlated, owing to its extremely high degeneracy of path lengths and transmission delays, which we will model as a directed percolation.","FID":106}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Trustees Of Boston University","Title":"CAREER: Mathematical Modeling and Computational Studies of Human Seizure Initiation and Spread","City":"Boston","State":"MA","Abstract":"Epilepsy - the condition of recurrent unprovoked seizures - is a brain disorder that affects 3 million people in the United States. Although the symptoms of epilepsy have been observed for millennia, the brain processes that support human seizures remain poorly understood. This lack of understanding has a profound clinical impact; in one-third of patients with epilepsy, seizures are not adequately controlled. Animal studies provide powerful methods to uncover the potential mechanisms for epilepsy, yet how the results from these studies relate to human epilepsy remains unclear. Although some mechanisms of epilepsy may be consistent in animal models and humans, differences occur, and these differences are critical to understanding and treating human epilepsy. The PI's goal is to improve understanding of the mechanisms that drive human seizures and thereby advance therapeutic management of this disease. To do so, brain voltage recordings made directly from human patients will be analyzed. Motivated by these patient data, mathematical models will be developed that describe the activity of individual neurons and small populations of interacting neurons. The mathematical models will then be used to study the biological mechanisms that support the different brain voltage rhythms that appear during seizure, and how these rhythms move across the surface of the brain. Ultimately, these mathematical models will provide new insights into human epilepsy, and help identify novel approaches to improve patient care. The PI will also include integration of research data and methods into an undergraduate course in computational neuroscience, publish a textbook and online course in neuronal data analysis, and provide undergraduate and graduate research training in computational neuroscience, with a specific emphasis on clinical data and computational modeling.<br /><br />The PI aims to improve understanding of the ionic and neuronal mechanisms that govern the brain's stereotyped spatiotemporal dynamics during human seizure. To do so, a computational modeling framework will be developed that incorporates individual neuron dynamics in cortical and subcortical structures and ion concentration dynamics in the extracellular space. Model behavior will be explored through simulation and dynamical systems techniques, and model features will be constrained to match microelectrode array recordings of seizures in human patients. The modeling framework will be used to test the hypothesized scenario that a class of cortical interneurons serve as the first line of defense against the outbreak of seizure, but eventually fails upon entering depolarization block. Concomitant with this failure, another circuit activates to the support large amplitude, spike-and-wave dynamics, which appear as traveling waves that sweep across the cortical surface. Two main research goals are the focus of the project. First the modeling of human seizure data will provide new insights into the mechanisms of medically refractory epilepsy, and help identify biological targets for novel pharmacological approaches to improve patient care. Second, to understand brain function and dysfunction, a deeper knowledge of cortical and subcortical neuronal dynamics combined with ion concentration dynamics is required. In this project, the stereotyped dynamical state of seizure motivates models that implement these dynamics to examine principles that support spatiotemporal patterns in the human brain. Educationally the PI will develop new interdisciplinary training in computational neuroscience. This will be done through integration of research data, analysis methods and computational technology in the undergraduate classroom, publication of a textbook and development of an online course describing cases studies in neural data analysis, and directed graduate and undergraduate research in computational neuroscience.","FID":107}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Trustees Of Boston University","Title":"Interaction of Time Scales in Forced Rhythmic Networks of Neurons","City":"Boston","State":"MA","Abstract":"It is now well accepted that cognitive functions are supported by activity dispersed throughout the brain, and that signals are passed among participating regions of the brain. Indeed, there is an active direction of study, known as connectomics, that seeks to find such connections on multiple spatial scales. It is not sufficient, however, to find what regions are connected. Rather it is important to determine how and in what directions regions are connected. How are signals conveyed and acted upon as part of a neural computational process? To understand such neural computations, it is necessary to understand how input patterns of signals in space and time are processed at the target network. This is a huge scientific program in which mathematics and modeling can play a central role in guiding experiments. The aim of this research is to produce a body of work that is representative of the general issues that are encountered in adding input that has timing structure to networks exhibiting rhythmic structure. From such a body of examples, a goal of this project is to search for general principles about networks of neurons with external input. Such forced networks are far more complex than the well-studied phenomena of simple forced oscillators. This project will support two graduate students and will be carried out within the context of the Cognitive Rhythms Collaborative, a NSF-supported group of more than two dozen labs (mostly) in the Boston area working on brain dynamics and cognition. The CRC is designed to facilitate collaborations among its many groups, with special attention to the graduate students and postdocs of these groups. <br /><br />This project is concerned with the effects of input signals with multiple time scales on target networks of neurons that also have multiple time scales. From the huge number of examples of these phenomena manifest in the nervous system, this research is focused on two of particular biological importance. The first is the interaction of gamma and theta rhythms, mainly in hippocampal networks, with inputs from other parts of the hippocampus and neocortex also carrying such temporal patterns. The second concerns a rhythm that has been experimentally and computationally investigated in a region of parietal cortex in vitro; parietal cortices are known to be hubs of connections, with inputs from many other areas. The particular rhythm in question arises as an after-effect of stimulation, and has been shown computationally to change the network response to later tonic excitation. This research will improve understanding of the effect on a network displaying this rhythm of input with more complex spectral properties, such as inputs from other brain regions. The networks involved have both excitatory and inhibitory cells, sometimes with more than one kind of inhibitory cell producing multiple time scales in the target network.","FID":108}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Trustees Of Boston University","Title":"Collaborative Research: Unraveling Cerebral Connectivity with Diffusion MRI, Microscopy and Statistical Physics","City":"Boston","State":"MA","Abstract":"A better understanding of the relationship between brain structure and function is an integral component of the on-going efforts aimed at developing a better understanding of the human mind. Fundamental research is required to accelerate the development of new technologies for neuroscience and near engineering in order to address important societal needs with respect to the development of new ways to treat, prevent, and cure brain disorders. In this larger context, this collaborative project will extend methods of statistical physics to bridge from microscopic neurobiological observations of neurons, axons and dendrites to the mesoscopic images of brain organization seen in diffusion MRI images of the entire primate brain. A particular focus will be to address the question of how the processes of the brain might exploit this special architecture for the representation and processing of information, and in particular, how this regular structure might support time-coding and synchronization of information across the brain.<br /><br />Joining a physics laboratory, a neurobiology laboratory, and an MRI laboratory, this team will investigates the hypothesis that brain connectivity is geometrically organized, with connectivity generally aligned with the axes of a curved, but essentially orthogonal coordinate system or 3D grid. The idea that the brain of all species with bilateral symmetry is based on an orthogonal plan is not new. It has been recognized in embryology and evolutionary biology for nearly 100 years and more recently has been validated in detail in studies of gene expression. Preliminary studies have suggested that this orthogonal motif pervades the structure of the brain, and particularly connectivity, from macroscopic down to a cellular level. In this interdisciplinary project, the investigators will quantify this phenomenon by looking at structural data from both diffusion MRI and advanced methods of 3D light microscopy and then apply the ideas and tools of condensed matter physics to characterize the structure and circuits of the brain as organized matter. As a first example, having observed 3 orthogonal fiber directions at each point in the brain that vary smoothly, it is natural to model this as a liquid crystal with a deformation energy and temperature. Then, one can investigate its scaling in the brain, and transitions such as those from white matter to gray matter. Functionally, we hypothesize that this rectilinear grid, may provide a new mechanism for neural activity to be temporally correlated, owing to its extremely high degeneracy of path lengths and transmission delays, which we will model as a directed percolation.","FID":109}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Children'S Hospital Corporation","Title":"Tools for Cells and Circuits","City":"Boston","State":"MA","Abstract":"Generating Multiple Circuit and Neuron Type Specific AAV Vectors With Cross-Species Applicability","FID":110}},{"geometry":{"x":-7915484.3913,"y":5216082.6928,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Massachusetts Institute Of Technology","Title":"Tools for Cells and Circuits","City":"Cambridge","State":"MA","Abstract":"Anterograde monosynaptic tracing","FID":111}},{"geometry":{"x":-7992982.945800001,"y":5200519.361199997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Univ Of Massachusetts Med Sch Worcester","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Worcester","State":"MA","Abstract":"Fluorescent Sensors for Imaging External Potassium in the Brain","FID":112}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Boston University (Charles River Campus)","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Boston","State":"MA","Abstract":"Ultra-miniaturized single fiber probe for functional brain imaging in freely moving animals","FID":113}},{"geometry":{"x":-7915484.3913,"y":5216082.6928,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Charles Stark Draper Laboratory","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Cambridge","State":"MA","Abstract":"Neural Monitoring with Magnetically-Focused Electrical Impedance Tomography (mf-EIT)","FID":114}},{"geometry":{"x":-7915484.3913,"y":5216082.6928,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Broad Institute, Inc.","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Cambridge","State":"MA","Abstract":"LOCATER: Large-scale Observation of Cellular Activity Through Exosomal Reporters","FID":115}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Boston University (Charles River Campus)","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Boston","State":"MA","Abstract":"Multiplexed Multiphoton Interrogation of Brain Connectomics","FID":116}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Massachusetts General Hospital","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Boston","State":"MA","Abstract":"Capabilities of MRI-Based Neural Current Imaging for Human Brain Mapping","FID":117}},{"geometry":{"x":-7915484.3913,"y":5216082.6928,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Harvard Medical School","Title":"Large-Scale Recording-Modulation - New Technologies","City":"Cambridge","State":"MA","Abstract":"Novel optrodes for large-scale electrophysiology and site-specific stimulation","FID":118}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Massachusetts General Hospital","Title":"Next Generation Human Invasive Devices","City":"Boston","State":"MA","Abstract":"High-Bandwidth Wireless Interfaces for Continuous Human Intracortical Recording","FID":119}},{"geometry":{"x":-7915484.3913,"y":5216082.6928,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Massachusetts Institute Of Technology","Title":"Next Generation Human Imaging","City":"Cambridge","State":"MA","Abstract":"Toward functional molecular neuroimaging using vasoactive probes in human subjects.","FID":120}},{"geometry":{"x":-7909999.931500001,"y":5214857.660899997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Children'S Hospital Corporation","Title":"Next Generation Human Imaging","City":"Boston","State":"MA","Abstract":"Sonoelectric tomography (SET): High-resolution noninvasive neuronal current tomography","FID":121}},{"geometry":{"x":-7915484.3913,"y":5216082.6928,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Harvard Medical School","Title":"Understanding Neural Circuits","City":"Cambridge","State":"MA","Abstract":"Lagging or Leading? Linking Substantia Nigra Activity to Spontaneous Motor Sequences","FID":122}},{"geometry":{"x":-8528103.7958,"y":4763380.9733000025,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Johns Hopkins University","Title":"Tools for Cells and Circuits","City":"Baltimore","State":"MD","Abstract":"Intrabody-dependent activation of cell-specific gene expression in CNS","FID":123}},{"geometry":{"x":-8528103.7958,"y":4763380.9733000025,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Hugo W. Moser Res Inst Kennedy Krieger","Title":"Next Generation Human Imaging","City":"Baltimore","State":"MD","Abstract":"Virtual Brain Electrode (VIBE) for Imaging Neuronal Activity","FID":124}},{"geometry":{"x":-8528103.7958,"y":4763380.9733000025,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Johns Hopkins University","Title":"ElectRx","City":"Baltimore","State":"MD","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":125}},{"geometry":{"x":-8556833.1204,"y":4751689.674900003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Bts Software Solutions, Llc","Title":"Revolutionizing Prosthetics","City":"Columbia","State":"MD","Abstract":"Develop advanced prosthetic arm systems and methods for restoration of near-natural movement and control","FID":126}},{"geometry":{"x":-8564617.3713,"y":4718910.748199999,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Maryland College Park","Title":"US-German Research Proposal: Collaborative Research: Field Potentials in the Auditory System","City":"College Park","State":"MD","Abstract":"The goal of the project is to provide a better understanding of what neural processes make up extracellular potentials recorded from brain, like the electroencephalogram (EEG). Although recorded in many settings, these potentials are poorly understood. Yet, they are clinically important; for instance, they are used for diagnosis of epilepsy and early detection of deafness. Development of differential diagnostic tools depends on understanding what brain components contribute to the recorded potentials. The investigators use a combination of quantitative modeling and recordings from the auditory system of the Barn Owl to gain insight into the connection between field potentials and their neuronal generators. In addition to better understanding of a widely used diagnostic tool, a further societally relevant outcome of the project lies in training women in Science, Technology, Engineering, and Mathematics. The U.S. and the German laboratories in this international collaboration have a strong commitment to science education and a well-established track record of training research fellows, as well as high school students and undergraduates from diverse backgrounds. <br /><br />Extracellular field potentials are typically generated by various neuronal sources, making their interpretation difficult. They are, however, clinically important, with applications ranging from diagnostics to brain-computer interfaces. In the auditory system, for example, the auditory evoked potential, also called the auditory brainstem response (ABR) is widely used for newborn hearing screening but little is known how specific nuclei contribute to it structure. Motivated by clinical relevance and theoretical importance of understanding extracellular field potentials, the international team applies a combined computational and neurophysiological investigation of the extracellular field potential in a bird model system. The targeted neural structure, the Nucleus Laminaris in the Barn Owl, is homogeneous and well organized, and allows direct access to a system with a large extracellular field potential. The investigators' models and experiments delineate the potential contributions of the three possible sources of the extracellular field potentials. The approach tightly integrates theory and experiments, to provide a fundamental understanding of the connection between the extracellular field potentials and their neuronal generators. The results from this collaborative cross-disciplinary effort will provide a basis for the interpretation of the clinically relevant ABR. A companion project is being funded by the German Ministry of Education and Research (BMBF).","FID":127}},{"geometry":{"x":-8528103.7958,"y":4763380.9733000025,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Johns Hopkins University","Title":"Collaborative Research: Integrating neural interfaces and machine intelligence for advanced neural prosthetics","City":"Baltimore","State":"MD","Abstract":"Brain-machine interfaces (BMI) read signals directly from the brain to control external devices such as robotic limbs. While this technology has great potential to benefit people who are paralyzed, BMIs often have poor performance because they use noisy, low-level signals to simultaneously control many aspects of the robotic limb's movements. In contrast, this project will address this shortcoming by reading high-level intents from the brain in order to control an intelligent robotic system. These changes reflect cutting-edge advances in neuroscience and machine intelligence and will require close cooperation between scientists, engineers, and physicians. The project aims to leverage expertise across these diverse fields in order to generate significant improvements in BMI technology to advance the national health, increase scientific understanding of the brain, and lead to dramatic improvements in the quality of life for these severely disabled persons.<br /><br />This collaborative project will decode high-level cognitive actions from neural signals recorded in the parietal cortex of a tetraplegic human, then carry out those intents using a smart robotic prosthesis. Persons with tetraplegia who have multielectrode arrays (MEA) implanted in reach and grasp areas of the posterior parietal cortex (PPC), will participate in experiments to explore the neural representation of cognitive intentions in human PPC including object selection, action intention, and neural control of robotic limbs. Experimental results will be used to construct BMI control algorithms optimized to decode these cognitive signals. In parallel, a modular, semi-autonomous robotic prosthesis will be developed that can identify household objects and plan reach-and-grasp movements to manipulate or transport the objects. These scientific and technological efforts will be supported by continued clinical care of the tetraplegic participants. The study will explore increasingly capable iterations of the BMI system, culminating in testing of the fully developed BMI system in the participants' own home environment where they will practice activities of daily living. The resulting system will leverage deep insights in cognitive neuroscience and advanced capabilities in machine sensing and robotic control systems to substantially improve the ease of use and capability of brain-machine interfaces.","FID":128}},{"geometry":{"x":-8564617.3713,"y":4718910.748199999,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Maryland College Park","Title":"Workshop: Bridging Neuroscience and Learning","City":"College Park","State":"MD","Abstract":"This award will support the conduct of a workshop focused on identifying and evaluating the scientific basis for neuroscience-based learning interventions. The workshop will bring together leading researchers who are working at the intersection of neuro-, cognitive, and educational sciences to address questions pertaining to the theoretical, empirical and methodological bases of interventions and technologies that purport to enhance learning and memory. The workshop will take place in Washington, D.C., in January 2015.<br /><br />The goals of the workshop are to (a) identify the current state of effective learning interventions and technologies; (b) discuss methodological and statistical challenges that have impeded scientific work in this area and propose solutions to these challenges; and (c) discuss ways of effectively and accurately communicating the scientific literature on neuroscience-based interventions to the broader public. A summary report will be produced that details the products of the discussion and that highlights prospects identified for evidence-based learning techniques based on neuroscientific principles.","FID":129}},{"geometry":{"x":-9436347.0647,"y":5403323.226800002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Central Michigan University","Title":"BRAIN EAGER: Genetically Encoded Light Sources for Non-Invasive Optogenetics","City":"Mount Pleasant","State":"MI","Abstract":"PI: Hochgeschwender, Ute H.<br />Proposal: 1450216<br />Title: BRAIN EAGER: Genetically Encoded Light Sources for Non-Invasive Optogenetics<br /><br />Significance<br />The realization of light-driven genetically targeted neuronal activation and silencing has led to unprecedented possibilities in manipulating neuronal activity in the behaving experimental animal.<br />However, translation of this approach into the clinical arena for potential therapeutic applications is complicated by the need for implanting optical fibers in the brain as the light source for activating lightsensing opsins. This proposal describes an integrated research, education, and outreach program which focuses on developing a new generation of genetically encoded light sources for non-invasive manipulation of optogenetic sensors. If successful this will be a key threshold advance that will provide the foundation for new technologies enabling minimally invasive and highly efficient diagnostics and therapies. Currently there are no alternative approaches which would achieve, non-invasively, the full range of photonic control of neurons as proposed here.<br /><br />Technical Description<br />The investigators will build on the highly innovative concept of combining optogenetics with bioluminescence. To exploit the concept?s potential for non-invasive light activation of optogenetic sensors in clinical settings, they will utilize protein engineering to both improve light output and extend the emission spectrum of the luciferase by optimizing intramolecular bioluminescence resonance energy transfer (BRET) between Gaussia luciferase and various fluorescent proteins. They will test the novel constructs for their efficiency in activating channelrhodopsins and proton and chloride pumps in vitro. The development of these concepts and reagents will have potentially transformative and broad impacts on the implementations of optogenetics in medicine.","FID":130}},{"geometry":{"x":-9322836.7613,"y":5203331.103100002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Michigan Ann Arbor","Title":"Statistical Tools for Analyzing Multiple Networks","City":"Ann Arbor","State":"MI","Abstract":"The widespread use of functional magnetic resonance imaging (fMRI) and other neuroimaging technologies has given rise to a new field of brain connectomics, which studies patterns of connections between different regions of the brain. This project brings together the investigator's expertise on statistical analysis of networks and her collaboration with neuroscientists to develop new methods for simultaneous statistical analysis of multiple networks and apply them primarily to brain connectivity networks inferred from fMRI imaging of mentally ill and healthy patients, with the goal of using sound statistical inference to discover how their brains differ. The methods leverage underlying common structure to share information across networks and identify structural network features associated with disease status and other diagnostic assessments. <br /><br />The raw fMRI data collected from brain imaging are typically converted to network representations, which are then analyzed to find patterns of normal human brain activity as well as abnormalities associated with various mental disorders. Thus the data are essentially a sample of networks, one for each subject. However, the current use of network analysis tools in brain connectomics is typically confined to simple global summaries of the network; even more commonly, the network structure is ignored altogether in what is known as massively univariate analysis, which looks at each connection separately. At the same time, the networks community has developed a wealth of methods for analyzing the structure of a single network, for example, discovering communities, but there are hardly any statistical methods that can handle samples of networks in a way that both respects and exploits network structure. This project will bridge this gap by developing new statistical methodology for samples of networks, and applying it to problems in brain connectomics. Our first goal is developing methods to estimate the \"population mean\" (in particular the underlying communities) from a noisy sample of networks. This project proposes an EM-type algorithm which outperforms naive averaging by exploiting the underlying common structure. The second goal is designing new accurate classifiers for networks which can identify interpretable predictive features such as subnetworks by using penalties based on both spatial and network distances between edges. The third goal is developing new measures of network similarity inspired by canonical correlations, which can be used for both network classification and clustering, the latter especially important for discovering subtypes of brain connectivity disorders which manifest themselves as different subtypes of psychiatric disorders. This project will also investigate measures of variability of network structure and methods for predicting not only disease status, but more complex multivariate diagnostic assessments. Development of these methods will have direct impact on research in neuroscience and mental health, and this project will ensure the methods relevance and feasibility by working in close collaboration with two brain imaging labs and disseminating the results both in the statistics and the connectomics communities. The project will also contribute to training graduate students in both network analysis and brain connectomics.","FID":131}},{"geometry":{"x":-9404690.9132,"y":5272101.947499998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Michigan State University","Title":"Synthetic and Biological Studies of Chondroitin Sulfate Oligosaccharides and Glycopeptides","City":"East Lansing","State":"MI","Abstract":"With this award, the Chemistry of Life Processes Program in the Chemistry Division is funding Dr. Xuefei Huang from Michigan State University to study the synthesis and functions of chondroitin sulfate (CS) and chondroitin sulfate proteoglycans (CSPG). Carbohydrates play important roles in many biological processes. However, due to the lack of uniformity of complex carbohydrate structures in nature, it has been very challenging to thoroughly understand their function. This project will focus on one specific class of carbohydrates referred to as chondroitin sulfate (CS) and chondroitin sulfate proteoglycans (CSPG), chondroitin sulfate that is bonded to protein. New synthetic approaches will be developed to produce these complex molecules, which will greatly expand the range of structures that can be accessed through chemical synthesis. With these materials, it will be possible to establish the impact of different structures on the interactions of CS and CSPG with, for example, amyloid beta peptide, the precursor to the aggregates and plaques that are present in the brains of people with Alzheimer's disease. In addition, the engagement of graduate, undergraduate and high school researchers in this project will provide them with opportunities to be trained in the important and challenging field of complex carbohydrate synthesis. The results generated will provide a highlight for the power of synthetic chemistry, and how chemical synthesis can be utilized to address important biological problems. <br /><br />Chondroitin sulfate (CS) and chondroitin sulfate proteoglycans (CSPG) are involved in many important biological events including neural development, organ morphogenesis, inflammation, infection and beta amyloid plaque formation. The number and location of O-sulfates in CS and CSPG can significantly influence their biological properties. As naturally existing CS and CSPG contain heterogeneous sulfation patterns, it is highly challenging to decipher the detailed structure function relationship using CS and CSPG isolated from nature. Contradicting results have been reported in the literature. In order to overcome this problem and facilitate biological studies, synthetic methodologies will be developed to produce CS oligosaccharides and CSPG glycopeptides with well-defined sulfation patterns and structures. The utility of these compounds will be demonstrated in the study of CS/CSPG interactions with beta-amyloid peptide to investigate a potential mechanism for the formation of amyloid plaques, a pathological hallmark of Alzheimer's disease.","FID":132}},{"geometry":{"x":-9404690.9132,"y":5272101.947499998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Michigan State University","Title":"US-Iceland Workshop: The Neural Basis of Icelandic Language Processing","City":"East Lansing","State":"MI","Abstract":"Organized by Alan Beretta of Michigan State University, this workshop on the \"Neural Basis of Icelandic Language Processing\" aims to catalyze a suite of follow-on research collaborations to enhance our basic understanding of how human brains process language. Held in Reykjavik, the workshop will bring together scholars from U.S. institutions with their counterparts from the University of Iceland and its Institute of Linguistics to study the neural processing of Icelandic sentences. Together, the partners will focus on the relatively rare and complex linguistic constructions found in the Icelandic language with the goal of gaining new insights into the language-brain relationship. Based upon initial progress at the workshop, the U.S. and Icelandic researchers and participating U.S. graduate students plan to begin designing follow-on electrophysiological experiments to examine how the normally functioning brain responds, within milliseconds, to such rare Icelandic language phenomena. A significant body of research related to complex wording has provided us with a solid platform for understanding how brains process language. However, questions remain and these unusual Icelandic structures may allow scientists to go deeper into the remaining fundamental questions. If successful, results from new research also may have long-term implications for understanding language impairment caused by brain damage.<br /><br />By investigating singular aspects of the neural processing of Icelandic, the researchers hope to enhance theoretical understanding of the language-brain relation. Conspicuously unusual constructions used in Icelandic language processing have the potential to reveal more specifically how brains process complex words, for example, noun-noun compounds. New insights are expected to contribute to the design of future experiments with aphasic subjects to determine how processing these language phenomena is affected in damaged brains. Furthermore, deeper theoretical understanding in this domain can have the longer-term benefit of suggesting more focused treatment regimes for people suffering from language impairments following brain damage.","FID":133}},{"geometry":{"x":-9436347.0647,"y":5403323.226800002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Central Michigan University","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Mount Pleasant","State":"MI","Abstract":"Employing subcellular calcium to control membrane voltage","FID":134}},{"geometry":{"x":-9322836.7613,"y":5203331.103100002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Michigan","Title":"Large-Scale Recording-Modulation - New Technologies","City":"Ann Arbor","State":"MI","Abstract":"Carbon Thread Arrays for High Resolution Multi-Modal Analysis of Microcircuits","FID":135}},{"geometry":{"x":-1.03822040673E7,"y":5618221.276299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Minnesota","Title":"Tools for Cells and Circuits","City":"Minneapolis","State":"MN","Abstract":"Engineered viral tropism for cell-type specific manipulation of neuronal circuits","FID":136}},{"geometry":{"x":-1.02925829859E7,"y":5468432.688500002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Mayo Clinic Rochester","Title":"Next Generation Human Invasive Devices","City":"Rochester","State":"MN","Abstract":"Neurophysiologically Based Brain State Tracking & Modulation in Focal Epilepsy","FID":137}},{"geometry":{"x":-1.03822040673E7,"y":5618221.276299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Minnesota","Title":"Short Courses","City":"Minneapolis","State":"MN","Abstract":"CoSMo - Summer School in Computational Sensory-Motor Neuroscience","FID":138}},{"geometry":{"x":-1.03822040673E7,"y":5618221.276299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Minnesota-Twin Cities","Title":"UNS: Developing Serial Optical Coherence Scanning to Reveal White Matter Changes in SCA1","City":"Minneapolis","State":"MN","Abstract":"PI: Akkin, Taner <br />Proposal Number: 1510674<br /><br />The objective of this project is to develop an optical imaging technique to study the anatomical changes associated with spinocerebellar ataxia type 1 (SCA1), which is a fatal inherited neurodegenerative disease. Development of the optical technique will enable a comprehensive three-dimensional (3D) reconstruction of the brain and cerebellum, and support quantitative assessments on white matter content and organization. The obtained information may result in the identification of specific markers of the disease and support development of therapeutics in the future.<br /><br />Serial optical coherence scanning (SOCS) integrates a tissue slicer and a multi-contrast optical coherence tomography for large scale brain imaging at high resolution. It distinguishes white matter and gray matter, and visualizes nerve fiber tracts that are as small as a few tens of micrometers. The retardance contrast due to axonal birefringence highlights the nerve fibers, while the axis orientation contrast indicates their orientation in the plane. In addition, the Purkinje cells and microstructures in gray matter can be visualized by incorporating a microscope objective. The development of SOCS will include a calibration path for obtaining the absolute axis orientation of nerve fibers in the xy plane, and imaging at multiple illumination angles to extract the inclination angle of the fibers with respect to the z-axis. This would represent the fiber orientation in 3D. It will also allow for calculation of the true birefringence. SOCS will be used on three different SCA1 mice models. The investigators hypothesize that as disease progresses towards death of Purkinje cells in nonlethal (ATXN1-82Q) and lethal (SCA1-154Q/2Q) forms, it will manifest in the local and global characteristics of the white matter, which is the axonal and probably the disease carrying pathway to the brainstem and other brain regions. Neither the Purkinje cell death, nor the premature death of the animal occurs for ATXN1-30QD776 mice, which will serve as the control group. Comparative studies will result in better understanding of the SCA1. The project also aims to integrate the research effort with the educational activities that involve general public and students. An exhibit at the Science Museum of Minnesota will be developed for broad dissemination of knowledge to enhance understanding of biomedical optics and the optical imaging technology that allows for high resolution visualizations of the brain. The content will be incorporated in a biomedical optics course taken by both undergraduate and graduate students.","FID":139}},{"geometry":{"x":-1.03822040673E7,"y":5618221.276299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Minnesota-Twin Cities","Title":"IEEE EMBS BRAIN Grand Challenges Conference November 13-14, 2014, Washington, DC","City":"Minneapolis","State":"MN","Abstract":"PI: He, Bin <br />Proposal Number: 1458986<br />Institution: University of Minnesota-Twin Cities<br />Title: Workshop: IEEE EMBS BRAIN Grand Challenges Conference, November 13-14, 2014, Washington, DC<br /><br />The IEEE EMBS BRAIN Grand Challenges Conference will be organized during November 13, 2014 - November 14, 2014 in Washington DC. The goal of the Conference is to provide a platform for open discussion and debate joined by the international scientific community with regard to the road maps of addressing BRAIN grand challenges as discussed and identified by NSF and NIH workshops and advisory groups. Such public discussions are critical for the scientific community to engage so the visions on BRAIN grand challenges can be smoothly translated into research innovations in years to come. Of particular emphasis will be the engineering challenges for advanced brain research through advancing innovative neurotechnologies (BRAIN). This reflects the vision that technological innovations are key to major advances in BRAIN research. The broader impacts of the Conference will include recruiting and recognizing outstanding young investigators to/in BRAIN research, and facilitating their participation in addressing the BRAIN grand challenges in a highly integrative platform together with world leaders in BRAIN research and education. This award is being made jointly by two Programs. (1) Biomedical Engineering, in the Chemical, Bioengineering, Environmental and Transport Systems Division (Engineering Directorate); and (2) Emerging Frontiers in Research and Innovation (EFRI) (Engineering Directorate).<br /><br />The Conference will have plenary lectures and panel discussions in mapping neural circuits: micro and macro; understanding functional neural dynamics; controlling neural circuits and restoring function; and funding and translation in the BRAIN initiative. Keynote and plenary speakers will include thought leaders from academia, government and industry. An interactive poster session will also be organized, in which the scientific community will present their ideas and engage in discussions. To attract and recognize outstanding young investigators to the BRAIN initiative, a young investigator BRAIN awards competition will be held for students, postdoctoral fellows and assistant professors (or equivalent). These awards will be selected by a panel of international experts in BRAIN research. It is anticipated that the Conference will contribute to public debate and discussion on how to address the grand challenges in BRAIN initiative. It will lead to a better understanding of several issues including, but not limited to: how can we image the brain activity and function with high spatial and temporal resolution by developing novel noninvasive imaging technologies; how can we image neural circuits with greater spatio-temporal resolution; how can we manipulate neural circuits and brain networks so as to enhance our understanding of the brain function and treat brain disorders; what are the engineering innovations needed to address the grand challenges, such as innovative sensors, imaging technologies, informatics and computational techniques; and what are the challenges to involve more engineers to work together with neuroscientists to address BRAIN grand challenges.","FID":140}},{"geometry":{"x":-1.03822040673E7,"y":5618221.276299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Minnesota-Twin Cities","Title":"Collaborative Research: Cortical Spreading Depression and Ionic Electrodiffusion in the Brain","City":"Minneapolis","State":"MN","Abstract":"A major goal of this project is to gain a better understanding of cortical spreading depression. This is a disorder of the brain that is the basis of migraine aura and many other diseases of the brain including stroke and epilepsy. In this disorder the ionic environment of the brain is completely disrupted and the nerve cells turn silent, with a disturbance that spreads at speeds of two to five millimeters per minute across the brain. When this happens in the visual cortex, the brain area that processes visual information, the patient will perceive an aura, a temporary visual defect that slowly travels over the field of view. Migraine sufferers often perceive an aura (migraine aura) prior to a migraine attack. Better understanding the mechanisms of cortical spreading depression will thus help in management of migraine headache and many other pathological brain conditions. This research collaboration will train graduate students who will work on various aspects of the project. Summer schools will be held at Florida International University, which is a minority serving institution. Thus this project, accompanied with existing institutional efforts, has the potential to further the goal of increasing minority representation in the sciences. Further, this collaborative effort brings together experimentalists and theorists of diverse interests and strength, and therefore provides students with an ideal opportunity for professional growth.<br /><br />Cortical spreading depression is a massive redistribution of ionic concentrations in the brain that results in a localized temporary loss of neuronal function. This disturbance spreads through the brain at speeds of two to five millimeters per minute and is the physiological substrate of migraine aura. Although cortical spreading depression was first described over seventy years ago, the physiological mechanisms leading to the disturbance remains elusive, most likely due to the fact that it involves many biophysical processes. In this project, a comprehensive mathematical model and computational apparatus to simulate the phenomena will be constructed and validated with experimental data obtained at high spatial resolution. An important aspect of the mathematical model is that it takes into account ionic electro-diffusion, an effect that has not been properly considered in previous studies, and may also be relevant for illucidating mechanisms in many other neurophysiological settings. In particular, the effects of electro-diffusion on extracellular recordings, electroencephalography and magneto-encephalography signals will be studied, thereby improving analysis of these measurement modalities. Overall this research may have an impact in many other brain pathologies which are linked to these underlying biophysical processes.","FID":141}},{"geometry":{"x":-1.00409689173E7,"y":4668489.866099998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Washington University","Title":"Tools for Cells and Circuits","City":"St. Louis","State":"MO","Abstract":"AN INDUCIBLE MOLECULAR MEMORY SYSTEM TO RECORD TRANSIENT STATES OF CNS CELLS","FID":142}},{"geometry":{"x":-1.02785902395E7,"y":4714828.788900003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Missouri-Columbia","Title":"Short Courses","City":"Columbia","State":"MO","Abstract":"Interdisciplinary Training in Computational Neuroscience for Researchers from Graduate and Medical Students to Junior Faculty","FID":143}},{"geometry":{"x":-1.00409689173E7,"y":4668489.866099998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Washington University","Title":"ElectRx","City":"St. Louis","State":"MO","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":144}},{"geometry":{"x":-1.02785902395E7,"y":4714828.788900003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Missouri-Columbia","Title":"BRAIN EAGER: Novel Thermo-genetic Tools for Extrinsic Control of Neuronal Circuits","City":"Columbia","State":"MO","Abstract":"Brains can be thought of as networks of circuits. The neurons that make up these circuits interact to control behavior, but how the neurons do this is currently an open question. New tools are needed to learn how neuron networks produce behavior. One promising strategy would be to construct molecular switches that could flip neurons between active and inactive states. This project will investigate the potential to engineer a special group of proteins to make them serve as molecular switches that respond to changes in temperature. The proteins will be put into specific brain neurons of flies, and the fly's behaviors will be monitored in response to temperature changes that activate and deactivate the neurons. The fly is an accessible experimental model for these studies, and, additionally, what is learned in the fly brain will have broad relevance to other animal brains. The project will involve undergraduate and graduate students in the research and will provide them with interdisciplinary training in biophysics, neurophysiology, and behavior. Tools developed in the project have the potential to be used to understand other organ systems and will be shared with the wider scientific community. <br /><br /><br />Individual Gustatory Receptor (GR) gene family members will be examined for temperature-dependent effects on nerve cell function. In one set of experiments, these GRs will be expressed in both sensory and non-sensory neurons in Drosophila melanogaster and tested for temperature responsiveness in heat-box behavioral assays. In a second set of experiments, natural- and chimeric-GRs will be expressed in Xenopus oocytes and COS cells and tested for temperature- and voltage-dependent kinetics of ionic current. Finally, natural- and chimeric-GRs will be expressed in sensory neurons in Drosophila and cultured cells and examined for physiological effects using live calcium imaging analysis.","FID":145}},{"geometry":{"x":-1.00409689173E7,"y":4668489.866099998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Washington University","Title":"Towards Analysis and Control of Dynamic Brain States","City":"Saint Louis","State":"MO","Abstract":"The study of neural coding asks how the brain converts raw signals into usable information that allows us to see, hear and think. Studying the mechanisms of neural coding is a persistent scientific challenge that has important implications for uncovering the workings of the brain. This award supports fundamental research that will enable a new approach to studying neural coding from the perspective of engineering theory. This perspective recognizes that networks in the brain can be modeled in terms of their physics and, thus, studied using many of the same tools that are used to study complex engineered systems such as aircraft and power grids. However, the brain possesses a level of complexity that far exceeds those of typical engineered systems and, consequently, existing engineering approaches must be adapted and augmented to meet biological realities. By addressing these gaps, this research will lead to new methods in engineering, advances in neural technology, and new ways of studying human brain function. This research is highly multi-disciplinary, involving systems engineering, mathematics and neuroscience. As part of the award, several new initiatives will be pursued to facilitate dialogue across these disciplines and to foster increased participation of underrepresented groups in engineering and science through the establishment of summer research internships for local high school students.<br /><br />This award approaches neuronal networks through the lens of dynamical systems and control theory. This approach is based on the premise that understanding the input-output relationships of neuronal networks, mediated by their dynamics, will shed new light on fundamental questions in neuroscience, including the link between neural dynamics and information processing. In pursuit of this goal, the award focusses on two main objectives: First, neuroscientifically-motivated adaptions of systems theoretic properties, such as reachability, will be formulated so as to understand how dynamics govern neural input-output relationships. Since the connections in brain networks constantly adapt, emphasis will be placed on the notion of a brain state, which characterizes both the activity and the network structure at a given time. Second, control methods will be developed for the modulation of such states. To do so, a new class of objective functions will be defined in terms of the systems-theoretic properties conferred by the network. For example, such objectives will involve using controls to expand a network's reachable space, rather than just controlling its activity. The control input in this context may be quite general, and several specific scenarios, including neurostimulation, will be studied.","FID":146}},{"geometry":{"x":-1.00409689173E7,"y":4668489.866099998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Saint Louis University","Title":"Chemical Connectomics: Nonlinear Dynamics of Electrochemical Reaction Networks","City":"St Louis","State":"MO","Abstract":"With this award, the Chemical Structure, Dynamics and Mechanisms (CSDM-A) Program of the Division of Chemistry is funding Professor Istvan Z. Kiss of Saint Louis University to investigate complex, far-from-equilibrium charge transfer chemical reactions that take place on networks imposed by dynamic environments of electrochemical devices (e.g., sensors and batteries). The identification of organizing principles and experimental characterization of far-from-equilibrium systems have broad applications in physical, chemical, and biological systems. The investigation is relevant to needs of industrial applications of galvanic and electrolytic cells. The oscillatory electrochemical media test theories on synchronization and network dynamics that have importance in circadian rhythms and hypersynchronous neural discharges in epileptic seizures. The project includes outreach activities aimed at middle school, high school and college students and the general public through the \"Nonlinear Corner,\" and conveys novel scientific notions of nonlinear science and the emergence of complex, intelligent behavior of abiotic systems.<br /><br /> Professor Istvan Kiss and his research group address three specific aims that are based on fundamental scientific problems in analytical chemistry utilizing multi-electrodes, design specifics of batteries and electrolysis cells, and energy distribution networks: (1) Test the hypothesis that emergent electrochemical networks in multi-electrode microfluidic flow cells can describe the complex dynamical phenomena, (2) explore self-organized spatio-temporal behavior in cathode-anode multi-electrodes, and (3) explore the pattern formation of electrochemical reactions that take place on a designed network facilitated by a resistance interface. The construction of versatile emergent and engineered networks provides a new geometrical space for the chemical reactions to take place. The extraction of network topology contributes to the establishment of Chemical Connectomics, the science of connected reactions in dynamic environments.","FID":147}},{"geometry":{"x":-1.00409689173E7,"y":4668489.866099998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Washington University","Title":"Theoretical Approaches to Multi-Scale Complex Systems","City":"Saint Louis","State":"MO","Abstract":"NONTECHNICAL SUMMARY<br />This award supports theoretical and data-centric computational research and education with an aim to advance the understanding of complex materials. In a perfect crystal, periodically repeating a fundamental structural unit of atoms can generate the entire atomic structure of the material. The theoretical description of such a structure of atoms leads to the elegant explanation of many properties of crystalline or near crystalline materials. By contrast, in complex materials such as glasses, additional rich structures appear on length scales between the atomic and the macroscopic scales. These features make understanding a wide range of materials from ordinary window glass to high temperature superconductors which can conduct electricity without resistance challenging.<br /><br />A goal of this project is to seek and quantify important structures in glassy materials - not by looking for particular known patterns- but rather by an unbiased analysis of structural data while invoking general physical principles. To address this challenge, the PI will broaden network analysis and computer vision methods to pinpoint and quantify the salient features of complex materials across different scales of length and time. This project will introduce new mathematical techniques for studying complex heterogeneous dynamics of both classical and quantum systems. The research will be done in close contact with experimental research groups around the world. The theoretical and data intensive computational study, in combination with experimental observations, is expected to lead to a deeper understanding of the structure of complex materials and systems including neural circuits, and enable progress in other disciplines. The techniques developed in this award will enhance cross-fertilization between condensed matter physics and other areas with multi-scale architectures such as medical imaging, bioinformatics, and communication networks. In collaboration with experimental neuroscientists, the PI aims to apply theoretical and data-centric computational tools developed in the course of research on materials to the visual neural circuits of the brain. <br /><br />This project supports training graduate students as well as further developing courses on advanced statistical mechanics and quantum information. The PI will also engage high school and undergraduate students to design software packages that illustrate the use of some of the methods developed during the course of the research.<br /><br />TECHNICAL SUMMARY<br />This award supports theoretical and data-centric computational research and education in theoretical condensed matter physics of materials with complex structure. The PI aims to develop and explore a new framework involving empirical data combined with ideas from data mining and network theory, Fokker-Planck, and other methods, to systematically uncover natural structures across a broad range of spatial and temporal scales. Analysis of experimental data of structural glasses and complex electronic materials will be performed with the aid of methods developed in the course of the project. Research will, specifically, be conducted along several directions: (1) The PI aims to employ ideas from statistical mechanics and network theory to unveil natural building blocks in disparate complex materials. The analysis will be performed on both experimental and simulation results in various materials systems including metallic glass alloys and electronic systems. As a byproduct, new concepts and tools will be developed and applied to optimization as well as imaging problems of wide interest. In collaboration with neuroscientists, the PI plans to apply developed tools to the study of the structure of the circuitry of the visual system of the brain. (2) The project will probe for low temperature quantum dynamical heterogeneities in cuprate superconductors and other electronic systems through a direct analysis of experimental data. Novel quantum effects at high temperatures will be further investigated. (3) Fokker-Planck methods will be applied to the study of structure and evolution of viscous systems. (4) The PI will investigate the mechanical properties of complex systems, in particular how they may respond to external shear, and ascertain associated length scales.<br /><br />This project provides a multidisciplinary research environment and an opportunity for students to learn a multitude of valuable techniques, including: molecular dynamics, image and network analysis, and data mining, in the context of close connection to experiments. The PI aims to review and communicate current ideas in network science, statistical mechanics, and condensed matter physics to graduate students through new courses. He also plans to engage high school and undergraduate students to design software packages that illustrate the use of some of the methods developed during the course of the research.","FID":148}},{"geometry":{"x":-1.23601570208E7,"y":5729107.764700003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Montana State University - Bozeman","Title":"Large-Scale Recording-Modulation - Optimization","City":"Bozeman","State":"MT","Abstract":"Northern Lights collaboration for better 2-photon probes","FID":149}},{"geometry":{"x":-8782711.5025,"y":4299991.712399997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Duke University","Title":"Collaborative Research: Analysis of the Mammalian Olfactory Code","City":"Durham","State":"NC","Abstract":"This project was developed during a NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Chemistry of Life Processes program in the Chemistry Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Physics of Living Systems program in the Physics Division, the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Division of Biological Infrastructure, and the Division of Emerging Frontiers.<br /><br />The mammalian sense of smell is arguably the most complex sensory system in the animal kingdom. Hundreds of olfactory receptors are deployed to detect a vast array of chemicals with exquisite sensitivity in complex environments. This collaborative project combines biochemistry, neurobiology, genomics, mathematics and new technologies to understand how the mammalian olfactory system detects, encodes and extracts meaning from chemical stimuli. The goals of this project are to: (1) elucidate fundamental neural mechanisms for how chemical sensation turns into the perception of a smell; (2) produce a vast array of scientific resources to olfactory scientists; (3) provide valuable information for broader audiences, including for molecular evolution, chemical ecology, and flavor and fragrance communities; (4) establish new technologies and mathematical frameworks to study biological systems; and (5) facilitate applied chemical sensing technologies for environmental monitoring, food safety, and homeland security. The project also offers training opportunities from the high school to the postdoctoral trainee level, and educational opportunities and outreach through partnerships with local science museums as well as science learning centers and their media outlets.<br /><br />This project's efforts are organized around three aims that focus on how information about odor identity and odor valence (attractiveness/aversiveness) is encoded at the level of olfactory receptors (Aim 1); within the olfactory bulb, where odor information is first processed (Aim 2); and the cortical amygdala, where odor codes may integrate with other information streams (Aim 3). Completion of the project entails the development and use a broad array of innovative approaches that include mapping all human and mouse odorant receptors to the chemicals they bind, defining the innate valence of these chemicals using behavioral assays, mapping all odorant receptor projections to the olfactory bulb, functionally characterizing their neural representations in the olfactory bulb and cortical amygdala, and using novel mathematical approaches to understand the underlying structure of odor coding and olfactory neural circuits at the level of sensory neurons, olfactory bulb glomeruli, and amygdala. Progress towards each aim involves close collaborations between team members with diverse expertise, including molecular biology, behavioral neuroscience, in vivo functional imaging, and mathematical and theoretical analysis of complex datasets. The multidisciplinary strategy implemented here promises to lead to an integrated and comprehensive understanding of how mammals sense and make sense of their chemical environments.","FID":150}},{"geometry":{"x":-8782711.5025,"y":4299991.712399997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Duke University","Title":"US-French Research Proposal: Collaborative Research: Predicting Odorant-dependent and Independent Olfactory Neuron Activation Based on Receptor","City":"Durham","State":"NC","Abstract":"Smell is a powerful sense that can trigger intense emotion, stereotyped behaviors and durable memories. The sense offers an extraordinary opportunity to connect atomic-level objects (odorant molecules and smell receptors in the nose) to neural responses. This project will predict which smell receptors in the nose are activated by a given odor. To accomplish this goal, the team of investigators will apply computational approaches to develop chemical structure-based receptor models and test these models using odor molecules interacting with olfactory receptors. The success of the project will enable the team to understand more precisely how the brain perceives the external environment. The results will also have widespread and diverse industrial applications, including rational design of new flavors and fragrances and development of new biosensors for detecting various chemicals. Furthermore, this project will make broader impacts in training and educating high school, undergraduate, and graduate students in various disciplines as well as in outreaching activities.<br /><br />The complexity of the odor molecules, the large number of the smell receptors and combinatorial activation of the receptors make understanding odor coding an enormous challenge. This collaborative proposal represents the first of its kind that combines computational approaches with experimental measurements at both the receptor and the neuron level. Affinity calculations between odorants and the receptors, as well as the receptors' activation, will be obtained by nanosecond-scale simulations. Atomic-level simulations, initially assessed by experiments, will predict which odors would activate the receptors of interest. Comparisons between experimental findings and computational predictions will lead to a comprehensive computational model that converges with experimental data. <br /><br />A companion project is being funded by the French National Research Agency (ANR).","FID":151}},{"geometry":{"x":-8998840.3938,"y":4194208.3363000005,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of North Carolina At Charlotte","Title":"CPS: Synergy: Collaborative Research: Fault Tolerant Brain Implantable Cyber-Physical System","City":"Charlotte","State":"NC","Abstract":"CPS: Synergy: Collaborative Research: Fault Tolerant Brain Implantable Cyber-Physical System<br /><br />Epilepsy is one of the most common neurological disorders, affecting between 0.4% and 1% of the world's population. While seizures can be controlled in approximately two thirds of newly diagnosed patients through the use of one or more antiepileptic drugs (AEDs), the remainder experience seizures even on multiple medications. The primary impacts of the chronic condition of epilepsy on a patient are a lower quality of life, loss of productivity, comorbidities, and increased risk of death. Epilepsy is an intermittent brain disorder, and in localization-related epilepsy, which is the most common form of epilepsy, one or a few discrete brain areas (the seizure focus or seizure foci) are believed to be responsible for seizure initiation. More recent approaches with implantable electrical stimulation seizure control devices hold value as a therapeutic option for the control of seizures. These devices, directly or indirectly, target the seizure focus and seek to control its expression. In this project we will build a multichannel brain implantable device based on emerging cyber physical system (CPS) principles. This brain implantable CPS device will incorporate key design features to make the device dependable, scalable, composable, certifiable, and interoperable. The device will operate over the life of an animal, or a patient, and continuously record brain activity and stimulate the brain when seizure related activity is detected to abort an impending seizure.<br /><br />Episodic brain disorders such as epilepsy have a considerable impact on a patient's productivity and quality of life and may be life-threatening when seizures cannot be controlled with medications. The goal of this project is to create a second generation brain-implantable sensing and stimulating device (BISSD) based on emerging CPS principles and practice. The development of a BISSD as a exemplifies several defining aspects that inform and illustrate core CPS principles. First, to meet the important challenge of regulatory approval a composable, scalable and certifiable framework that supports testing in multiple species is proposed. Second, a BISSD must be wholly integrated with the patient and fully cognizant at every instant of brain state, including dynamic changes in both the normal and abnormal expression of brain physiology and therapeutic intervention. Thus, this project seeks a tight conjunction of the cyber solution that must monitor itself and monitor and stimulate the brain using implanted, adaptable, distributed, and networked electrodes, and the physical system which in this case is the intermittently failing human brain. Third, a BISSD must function for an extensive period of time, up to the life of the patient, because each surgery to place and retrieve a BISSD carries an attendant risk. This requirement necessitates a dependable solution, which this project seeks to reliably achieve through both an understanding of the brain's foreign body response and a unique hierarchical fault-tolerant design. Fourth, an advanced salient approaches to acquire, compress, and analyze sensor signals to achieve real-time monitoring and control of seizures is employed. This project should yield a powerful, scalable CPS framework for robust fault-tolerant implantable medical devices with real-time processing that can grow with advances in sensors, sensing modalities, time-series analysis, real-time computation, control, materials, power and knowledge of underlying biology. The USA has a competitive advantage in the control of seizures in medically refractory epilepsy. In the modern era, epilepsy surgery evolved in the USA in the 1970s and spread from here to other parts of the world. Similarly, the USA enjoys a competitive advantage in BISSDs, and success in this effort will enable the USA to build on and maintain this advantage. In addition to epilepsy, advances made here can be expected to benefit the treatment of other neurological and psychiatric brain disorders.","FID":152}},{"geometry":{"x":-8782711.5025,"y":4299991.712399997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Duke University","Title":"NCS-FO: Real-time optical readout and control of population neural activity with cellular resolution","City":"Durham","State":"NC","Abstract":"ECCS- Prop. No. 1533598<br /><br />PI: Gong, Yiyang <br />Institute: Duke University<br />Title: NCS-FO: Real-time optical readout and control of population neural activity with cellular resolution<br />Objective: <br />This project will develop a mechanism for simultaneously controlling and reading out neural activity when being activated by optogenetic techniques; this capability will surpass a previous limitation in neural studies. The proposal is separated into three aims: 1) develop calcium sensors and optogenetic channels active on different wavelength ranges to allow simultaneous readout and control, 2) develop a dual-beam two photon microscope, and 3) develop imaging software that can process neural activity in real-time. <br /><br />Nontechnical <br />Understanding neural function requires examining specific subsets of the vast numbers of neurons in the brain. Recently developed optogenetics tools, such as optogenetic stimulation and calcium imaging, have partially fulfilled the need to target these specific sets of neurons and study their function. These techniques deliver engineered genes to targeted neural populations, and use light to manipulate or measure neural activity. Current optogenetic tools lack the spatiotemporal resolution to causally study many individual neurons in parallel on fast time scales; they only make broad conclusions either on near-millimeter sized brain regions, or over the timescale of many action potentials. We propose to integrate the design and implementation of optical and genetic tools to greatly refine the scale of investigating neural activity. Specifically, we will create two optically independent channels: one channel for fast, spatially precise optical patterning to control individual neurons; and one channel for independent recording of neural activity from individual neurons. We will then integrate these two channels by creating software that instantaneously patterns optical excitation based on the optical recording. Integrative design and engineering of this expansive set of tools will enable neuroscientists to quickly manipulate and control large populations of single neurons, a capability that does not exist presently. Our technology will allow the community to directly explore how neural activity patterns of many individual neurons in one brain region drive downstream neural activity. This novel probing of functional connectivity is exactly the type of study needed to better understand the coordination of neural activity in healthy and diseased brains. Beyond the specific application of neuroscience, training students within our multidisciplinary setting will create the next generation of scientists capable of tackling the broad set of technical challenges facing society today. <br /><br /><br />Technical <br />Optical imaging of brain activity has steadily developed into a staple technique within neuroscience labs over the past decade. In combination with genetically encoded sensors of neural activity, optical methods enable genetic targeting and chronic, simultaneous imaging of many individual neurons. One significant weakness of existing optical techniques when compared to electrophysiology is the inability to simultaneously measure and control the activity of a neuron in real time. We propose to address this shortcoming by developing an optical imaging system and data processing software suite that will enable real-time optical readout of neural activity and real-time neural feedback via optical excitation, all with cellular level specificity and in parallel over a large population of neurons. This new ability to optically record and manipulate many genetically or functionally specified neurons individually will augment current studies using bulk neural activation or inhibition; the fine scale perturbations of neurons will tease apart the details of neural circuits. Specifically, we will engineer a set of optogenetic actuators, fluorescent sensors, and microscopy tools that will enable optical readout and control of neurons in different wavelength channels. We will also develop fast image processing algorithms that quickly convert images to neural activity of individual neurons, thereby enabling real-time control of neural activity based on the optical readout. Recently, improvements to these tools occurred independently. Our proposal will address the integrated development of the tool set, and effectively employ trade-offs between the individual components. For example, simultaneous engineering of the protein sensor, imaging processing software, and optical imaging hardware will optimize the readout fidelity. Similarly, joint design of the genetic tools' spectral separation and the optical spatiotemporal resolution will extend optical control precision. Integration of these developments to examine neural function at the cellular level is unprecedented: successful advancement of this research will enable novel examination of the brain and help guide targeted biomedical therapi","FID":153}},{"geometry":{"x":-8782711.5025,"y":4299991.712399997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Duke University","Title":"CAREER: Harnessing Nitrogen-Heteroatom Bonds for Unsaturated Carbon-Carbon Bond Difunctionalization","City":"Durham","State":"NC","Abstract":"With this CAREER Award, the Chemical Synthesis Program supports fundamental research to be carried out by Professor Qiu Wang at Duke University. Professor Wang will develop new synthetic routes to organic compounds that contain nitrogen. Organonitrogen compounds are widely distributed in nature and they display a broad range of biological activities. Efficient multistep processes are being developed to construct carbon-nitrogen bonds through the use of versatile intermediates. In addition to applications in biological and chemical science, this research has the potential to impact the pharmaceutical, chemical and agricultural industries through the creation of efficient routes leading from readily available starting materials to important nitrogen-containing synthetic intermediates. This research aims to provide broadly applicable strategies for the synthesis of more complex organic structures. To motivate young minds, Professor Wang will develop a training foundation directed at involving women and underrepresented minority students in cutting-edge chemical research. This educational program will encourage students to think creatively and collaboratively, building the skills necessary to undertake complex scientific and social challenges and encouraging students to pursue careers in scientific discovery. Toward this goal, Professor Wang will work with North Carolina local high schools and the Duke Service-Learning Program to provide opportunities for high school students to conduct hands-on experiments at the frontiers of chemistry research. This outreach program will recruit faculty, graduate students and undergraduate students as science ambassadors to visit local schools and to speak on their research. <br /><br />Professor Wang's research focuses on the direct introduction of 1,2-diamino-functionality onto diverse unsaturated carbon-carbon bonds. The project involves the study of reactivity in reagents bearing nitrogen-heteroatom bonds (N-X; X=Cl, Br, I, OR) with the goal of developing operationally simple and efficient amino-functionalization reactions, including (1) the amino-halogenation of arynes to prepare ortho-functionalized aminoarenes, (2) intramolecular amino-fluorination to prepare fluorinated aza-heterocycles, and (3) intra- and intermolecular alkene diamination reactions designed to prepare valuable vicinal diamines. Experimental studies are planned to provide insight into the mechanism and stereochemical outcome of these reactions, potentially guiding the design of second generation N-X to N-C transformations.","FID":154}},{"geometry":{"x":-8311589.379000001,"y":4918441.043700002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Princeton University","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Princeton","State":"NJ","Abstract":"Use of Calcium Indicator Proteins in Spike Counting Mode","FID":155}},{"geometry":{"x":-8287046.8916,"y":4938103.654799998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Rutgers University New Brunswick","Title":"UNS: Brain-on-a-chip for Traumatic Brain Injury Drug Discovery","City":"New Brunswick","State":"NJ","Abstract":"PI: Yarmush, Martin L. <br />Proposal Number: 1512170<br /><br />Traumatic brain injuries (TBI) are the leading cause of disability each year in the US and are also a major risk factor for epilepsy in both injured civilian and military populations. TBI dramatically reduces quality of life in affected patients and there are significant direct and indirect costs associated with TBI. While some drug TBI treatment protocols are under clinical review, none has been identified which can significantly attenuate the progression of events leading to neurological impairment. Improved in vitro screening methods are critical to expedite drug identification and development. Animal studies are both expensive and time consuming, but most in vitro approaches fail to recapitulate in vivo central nervous system inter-cellular connections and responses. Therefore, the goal of the proposed studies is to develop a novel high content \"Brain-on-a-Chip\" device, which integrates pairs of brain tissue slices and uses novel microfabrication and optical imaging tools, to identify drug candidates that can be used to treat TBI.<br /><br />Many recent studies indicate that mitochondrial dysfunction contributes to secondary TBI severity and associated axonal dysfunction. As such, the investigators aim to develop a high-content approach to screen mitochondrial drugs to alleviate post-TBI neuronal decay. An interdisciplinary team of science and engineering investigators will utilize microfabrication techniques to develop a \"Brain-on-a-Chip\" device which will be used to culture paired brain organotypic tissue slices with individual interconnecting axons that extend over microchannels. Strain injury will be introduced by pressurizing a cavity beneath the microchannels. Integrating a multi-electrode array (MEA) on-chip will enable precise and on-line identification of electrophysiological changes in response to injury. The investigators expect to assess how various strain injuries affect electrophysiological and biochemical responses between two organotypic slices using a novel dynamic optical imaging approach. By using microfabricated \"Brain-on-a-Chip\" arrays, the investigators will be able to screen, in parallel, drug candidates both individually and in combination, more efficiently than has been previously possible. Establishment of such a novel platform is significant, because it would accelerate the identification of molecular entities which control the injury response and, in concert, the development and screening of drug treatments for complex circuit disorders like TBI and epilepsy. The education plan includes high school, undergraduate, and graduate training components with a focus on underrepresented student education. Furthermore, industrial practitioners will be involved in bioengineering courses, which is an effective approach allowing student exposure to the industrial environment.","FID":156}},{"geometry":{"x":-8362222.889699999,"y":4857989.983400002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Rutgers University Camden","Title":"MRI: Acquisition of a femtosecond laser system to enable multiphoton polymerization, photoporation, and laser ablation in liquids research","City":"Camden","State":"NJ","Abstract":"Laser systems capable of generating ultra-short pulses have become a powerful tool for both fundamental research and advanced manufacturing processes. This MRI award supports the acquisition of a state-of-the-art femtosecond laser system (FLS) capable of emitting coherent light over a broad spectral range. The FLS enables potentially transformative multidisciplinary research leading to new green energy technologies and enhanced medical imaging with more functional nanoparticles, more effective gene therapy through knowledge of how to introduce genetic material into cells, and enhanced performance of microelectronic devices through development of new processes for fabricating ultra-small 3D devices. The instrumentation will dramatically expand the scope and significance of laser processing work in southern New Jersey. Students from several STEM majors will be involved in the research and the instrumentation facilitates efforts at Rutgers University-Camden to reach out to traditionally under-represented groups within the STEM fields.<br /><br />These projects include: (1) a fundamental study of the laser-material interactions associated with a laser-based method for the synthesis of nanoparticles. The benefits of this approach, dubbed laser ablation in liquids (LAL), are its foundations in green technology and capability of producing a wide variety of nanoparticles. This work will combine experimental and computational efforts to better understand the mechanisms leading to particle size and composition, both of which are critical parameters in nanoparticle functionality. (2) An investigation of the interactions between photoexcited particles and cell membranes found in nanoparticle-meditated photoporation. Gene therapy is rapidly becoming one of the most powerful techniques that medical practitioners have to fight disease. An important process in this therapy is transfection, i.e. introduction of genetic material into the cells. This project will ascertain how photoexcited nanoparticles generate transient pores within the cell membrane permitting the targeted introduction of genetic material. (3) Development of a comprehensive understanding of the factors leading to successful formation of 3D microstructures using multiphoton absorption polymerization (MAP). As an example, the researchers will investigate the fabrication of micro-fluidic heat exchanges that have sub-wavelength features. In this regard, photosensitive resins will be formulated that polymerize under exposure to intense light with wavelengths otherwise transparent to material; hence, allowing ultra-small 3D structures to be manufactured.","FID":157}},{"geometry":{"x":-8311589.379000001,"y":4918441.043700002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Princeton University","Title":"Collaborative Research: PoLS Student Research Network","City":"Princeton","State":"NJ","Abstract":"This collaborative research project, consisting of four institutions (Rice, Yale, UIUC and Princeton) aims to continue the Physics of Living Systems Student Research Network (PoLS SRN). This network has been in existence for four years and has had a dramatic impact on many graduate students, both in the US and abroad, working on the application of physical science techniques to living systems. These students now can participate in a global community that can help deal with the many complex issues involved in conducting research in such a new and inherently multidisciplinary field. These issues range from proper training, to gaining a broad perspective, to accessing technical expertise that may not be available at their home institution. In addition to the obvious broader impacts related to training of a research workforce, there are other broad impacts of this plan. Via the interaction of one of the PoLS nodes (Rice) with the biomedical community in Houston, students and faculty will be exposed to possible avenues whereby physics can contribute to human health issues. Funds to attract students from under-represented groups to network meetings will be available through the new funds administered by the newly proposed network coordinator. Also deas vetted by the PoLS SRN will be adapted to create student networks in other areas of science and engineering.<br /><br />There is by now little disagreement with the general notion that concepts and methods from physics have been a critical contributor to the increased understanding of the living world, and that its importance will be growing as the scientific world moves toward an ever more quantitative and predictive form of biology. Thus, the physics community clearly needs to train a new generation of scientists who can lead this effort, scientists who have the right mix of physics/mathematics rigor and broad knowledge of living systems from molecular scales on up. The PoLS SRN aims at creating a community of graduate students who can collectively help themselves and their mentors accelerate and enhance this training process. This is being done by a mix of in-person and virtual modes of communication, and this proposal is a plan to continue and expand these efforts; it will reach more students, improve the social networking portals, and make use of the complementary research agendas of the different network nodes to provide broad technical expertise. Doing all of this, will boost the intellectual level of the entire research field and convince the best students that the Physics of Living Systems is truly the most exciting research frontier in 21st century science.<br /><br />This project is being jointly supported by the Physics of Living Systems program in the Division of Physics, the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences, the Chemistry of Life Processes program in the Division of Chemistry, and the Cellular Dynamics and Function Program in the Division of Integrative Organismal Systems.","FID":158}},{"geometry":{"x":-8311589.379000001,"y":4918441.043700002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Princeton University","Title":"Collective Phenomena in Neural Population Codes","City":"Princeton","State":"NJ","Abstract":"In virtually every part of the brain, information about the sensory environment, internal body states, or intended movements is encoded by more than one neuron. This was apparent as early as the nineteenth century from the extensive interconnectivity of nearby neurons and continues to be apparent from numerous measurements of the tuning curves and correlation of nearby neurons. Despite its fundamental importance, population neural codes are poorly understood. In this project, the PI will combine large-scale neural recording methods with state-of-the-art theoretical analyses to study collective phenomena in population neural codes. The project will focus on the retina as a model system, where the quality and completeness of experimental data is the greatest. The project will give us a thorough and clear understanding of what are the \"ingredients\" needed at the population level to give rise to criticality, which will be important in generating hypotheses about what other regions of the brain might exhibit criticality in their population codes. It will also explore a novel hypothesis about how critical population states give rise to a discrete aspect of the neural code and one that is highly robust to neural noise. This could give us new insight into how we effortlessly divide the sensory world into objects. <br /><br />The PI has an extensive track record in multi-electrode recording from the vertebrate retina, along with applying maximum entropy models to analyze states of network activity. The PI hypothesizes that the retinal population code has an unusual and nontrivial structure that it analogous to the critical state in physical systems. This structure leads to the definition of a \"collective mode\" of neural activity, which is a set of neural activity states that groups visual stimuli into discrete classes. These collective modes constitute a novel hypothesis about population neural codes that is qualitatively different from the view of information encoding at the single-neuron level. The proposed projects aims are: understanding the origin of criticality, including studying the role of correlations in the stimulus, using adaptation to test how specifically retinal circuitry is tuned to give rise to criticality, studying the pattern and strength of correlation required for any network to give rise to criticality as well as formulating receptive field models to see what degrees of overlap and functional heterogeneity are required in defining collective modes of neural activity and studying what stimuli they encode and how reliably they are activated by a given visual stimulus. The broader impacts of the proposed work lie along three distinct directions:(i) the potential to develop new concepts about population neural codes that could prove applicable across many different brain regions; (ii) the development and dissemination of software to perform maximum entropy fits to neural data, which could help spur on the research programs of many labs that use these methods to analyze neural populations; (iii) the broadening of our ideas about critical systems in physics to include the kind of asymmetric, intermediate cases found in biology.<br /><br />This project is being jointly supported by the Physics of Living Systems program in the Division of Physics and the Cellular Dynamics and Function Program in the Division of Integrative Organismal Systems.","FID":159}},{"geometry":{"x":-8311589.379000001,"y":4918441.043700002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Princeton University","Title":"NCS-FO: Collaborative Research: Sleep's role in determining the fate of individual memories","City":"Princeton","State":"NJ","Abstract":"Identifying the cognitive, computational and neural mechanisms responsible for determining why some memories survive when others fade is one of the many grand challenges facing researchers of the human mind and brain. It is widely understood that sleep plays a critical role in long-term remembering, yet what exactly happens during sleep to affect the persistence of memories remains largely unknown. This project brings together a team of researchers who will integrate multiple independent lines of work in cognitive neuroscience, cognitive psychology, and computer science in order to investigate the precise mechanisms undergone by recently-formed memory representations as a person sleeps and how these mechanisms determine which memories survive and which fade. The proposed integration of cutting-edge neural data analysis methods for EEG and neuroimaging data, basic human memory theory, and neural network modeling make possible the ability to non-invasively track individual memories in the human brain as they compete with each other and are modified during sleep. The potential advances from this work could impact education, training situations, and public health by facilitating the development of new strategies for ensuring that important memories survive after initial learning.<br /><br />Research suggests that memories compete for neural space such that reactivating one particular memory can exert \"collateral damage\" on other related memories. In other words, accessing one memory can come at the expense of later being able to access other nearby memories in the network space. The proposed studies test the hypothesis that importance shapes neural dynamics during sleep by selectively boosting memory reactivation; this boost ensures that important memories out-compete related memories during sleep, resulting in strengthening of important memories and weakening of less-important memories. To test this hypothesis, competition between memories will be elicited during sleep by playing sound cues, each of which was linked (during wake) to two different picture-location memories. Multiple interlocking approaches will track how memory competition during sleep shapes a memory's persistence versus fading. Neural network models will be used to generate predictions about how reward responses during encoding shape competitive dynamics during sleep, and how these competitive dynamics determine the eventual fates of competing memories. Predictions will be tested by using fMRI to measure neural activity associated with reward processing during encoding, EEG to measure brain activity during sleep, and pattern classifiers to decode memory activation from the sleep EEG data. Observations of competitive dynamics during sleep will then be related to later memory performance and to multivariate fMRI measures of memory change. The project has the potential to provide, for the first time, a comprehensive look \"under the hood\" at the life of a memory as it is acquired, processed during sleep, and eventually recalled. Pivotal knowledge will be gained about how variance in reward processing at encoding influences sleep replay dynamics, and about how sleep replay dynamics affect subsequent memory performance and the structure of neural representations.","FID":160}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Weill Medical Coll Of Cornell Univ","Title":"Tools for Cells and Circuits","City":"New York","State":"NY","Abstract":"LIPS: A novel technology for spatial and temporal control of protein synthesis in dendritic spines","FID":161}},{"geometry":{"x":-8141898.2531,"y":4999492.6976,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"State University New York Stony Brook","Title":"Tools for Cells and Circuits","City":"Stony Brook","State":"NY","Abstract":"Genetic tools and imaging technology for mapping cholinergic engrams of anxiety","FID":162}},{"geometry":{"x":-8177341.3641,"y":4993285.748999998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Cold Spring Harbor Laboratory","Title":"Tools for Cells and Circuits","City":"Cold Spring Harbor","State":"NY","Abstract":"SYNPLA: A scaleable method for monitoring circuit-specific learning-induced changes in synaptic strength","FID":163}},{"geometry":{"x":-8780709.6401,"y":5294551.337899998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"State University Of New York At Buffalo","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Buffalo","State":"NY","Abstract":"Potentiometric photoacoustic imaging of brain activity enabled by near infrared to visible light converting nanoparticles","FID":164}},{"geometry":{"x":-8515435.3964,"y":5227196.266999997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Cornell University","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Ithaca","State":"NY","Abstract":"Wavefront sensor for deep imaging of mouse brain","FID":165}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Columbia Univ New York Morningside","Title":"Large-Scale Recording-Modulation - Optimization","City":"New York","State":"NY","Abstract":"SCAPE microscopy for high-speed in-vivo volumetric microscopy in behaving organisms","FID":166}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Rockefeller University","Title":"Large-Scale Recording-Modulation - Optimization","City":"New York","State":"NY","Abstract":"High-speed volumetric imaging of neuronal network activity at depth using Multiplexed Scanned Temporal Focusing (MuST)","FID":167}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Weill Medical Coll Of Cornell Univ","Title":"Next Generation Human Invasive Devices","City":"New York","State":"NY","Abstract":"Central thalamic stimulation for traumatic brain injury","FID":168}},{"geometry":{"x":-8177341.3641,"y":4993285.748999998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Cold Spring Harbor Laboratory","Title":"Understanding Neural Circuits","City":"Cold Spring Harbor","State":"NY","Abstract":"Computational and circuit mechanisms for information transmission in the brain","FID":169}},{"geometry":{"x":-8204042.5967,"y":4982625.125600003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"The Feinstein Institute For Medical Research","Title":"ElectRx","City":"Manhasset","State":"NY","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":170}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Rockefeller University","Title":"Collaborative Research: Analysis of the Mammalian Olfactory Code","City":"New York","State":"NY","Abstract":"This project was developed during a NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Chemistry of Life Processes program in the Chemistry Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Physics of Living Systems program in the Physics Division, the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Division of Biological Infrastructure, and the Division of Emerging Frontiers.<br /><br />The mammalian sense of smell is arguably the most complex sensory system in the animal kingdom. Hundreds of olfactory receptors are deployed to detect a vast array of chemicals with exquisite sensitivity in complex environments. This collaborative project combines biochemistry, neurobiology, genomics, mathematics and new technologies to understand how the mammalian olfactory system detects, encodes and extracts meaning from chemical stimuli. The goals of this project are to: (1) elucidate fundamental neural mechanisms for how chemical sensation turns into the perception of a smell; (2) produce a vast array of scientific resources to olfactory scientists; (3) provide valuable information for broader audiences, including for molecular evolution, chemical ecology, and flavor and fragrance communities; (4) establish new technologies and mathematical frameworks to study biological systems; and (5) facilitate applied chemical sensing technologies for environmental monitoring, food safety, and homeland security. The project also offers training opportunities from the high school to the postdoctoral trainee level, and educational opportunities and outreach through partnerships with local science museums as well as science learning centers and their media outlets.<br /><br />This project's efforts are organized around three aims that focus on how information about odor identity and odor valence (attractiveness/aversiveness) is encoded at the level of olfactory receptors (Aim 1); within the olfactory bulb, where odor information is first processed (Aim 2); and the cortical amygdala, where odor codes may integrate with other information streams (Aim 3). Completion of the project entails the development and use a broad array of innovative approaches that include mapping all human and mouse odorant receptors to the chemicals they bind, defining the innate valence of these chemicals using behavioral assays, mapping all odorant receptor projections to the olfactory bulb, functionally characterizing their neural representations in the olfactory bulb and cortical amygdala, and using novel mathematical approaches to understand the underlying structure of odor coding and olfactory neural circuits at the level of sensory neurons, olfactory bulb glomeruli, and amygdala. Progress towards each aim involves close collaborations between team members with diverse expertise, including molecular biology, behavioral neuroscience, in vivo functional imaging, and mathematical and theoretical analysis of complex datasets. The multidisciplinary strategy implemented here promises to lead to an integrated and comprehensive understanding of how mammals sense and make sense of their chemical environments.","FID":171}},{"geometry":{"x":-8515435.3964,"y":5227196.266999997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Cornell University","Title":"BRAIN EAGER: Using Optogenetic Techniques in Combination with Free Flight Perturbations to Elucidate Neural Structure Governing Flight Control in D. Melanogaster","City":"Ithaca","State":"NY","Abstract":"Forging the link between individual neuron function and the behavior of collections of neurons that can produce complex behaviors is the central goal of contemporary neuroscience. The path towards achieving this goal is being revolutionized by genetic techniques that allow for manipulation of the activity of neurons and measurement of the effect on behavior. Flight behavior in the fruit fly, Drosophila, is highly suitable for this combined analysis, since flies can be genetically manipulated very easily and their rich set of free flight behaviors can be quantitatively characterized in great detail. This project will use this approach to unravel the design and operation of a remarkable neural circuit responsible for giving flies one of the fastest response times in the animal kingdom and controlling their high speed maneuvering capabilities. Using small magnets attached to the flies and applied magnetic fields, flies will be subjected to forces in midair that alter their flight. By turning on and off the neurons in the control circuit that governs their response to such forces and determining the resulting change in their wing motions, the role that each individual neuron plays in the neural circuit that governs the recovery of these insects to the experimental perturbation will be determined. More broadly this work will lay the framework for a general powerful approach for interrogating and building an understanding of many other complex neural circuits. Moreover, the discoveries made will inform design principles for the development of efficient control strategies that can be used in robots. This pipeline for discovery will be publicized through conference meetings, publications, and workshops. In addition, the analysis routines and resulting data will be made available through the Principal Investigator's group web site. <br /><br />The flight of fruit flies (Drosophila) provides a rich set of free flight behaviors that can be quantitatively characterized in great detail using methods recently developed by the PI. Towards this end, this project will develop a platform in which each neuron in this circuit can be manipulated using optogenetics and the altered behavioral response quantified, with the aim of dissecting with unprecedented detail a behaviorally vital yet poorly understood neural circuit. Crucially, the approach taken entails using large empirical data sets of flight kinematics in conjunction with the mathematical theory of dynamical systems to generate reduced order models. These models will be used to guide the experiment design and interpretation of the resulting kinematic data. Application of this approach to motor-neurons will be used to elucidate the role of specific steering muscles in the flight control process. Application of this approach to the inter-neurons, which relay sensory responses to the motor-neurons, is being used to elucidate the design and function of the neural control circuit that determines the fly's response to mid-air perturbations. More broadly the complexity and hierarchical layout of the machinery necessary for insect flight is typical of other complex neural circuits.","FID":172}},{"geometry":{"x":-8177341.3641,"y":4993285.748999998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Cold Spring Harbor Laboratory","Title":"BRAIN EAGER: Novel Targeting Strategies for Projection-specific Mapping of Neurons","City":"Cold Spring Harbor","State":"NY","Abstract":"A central goal in neuroscience is to understand behavior in terms of the activity and connectivity of specific neurons. Anatomical tracings have revealed the mesoscale connections in the brain, but this dataset lacks functional utility without the ability to behaviorally study neurons with specific connections to other brain regions. Recently, a number of technological advances have enabled these types of experiments, including re-engineered viruses to target specific neuron types and deliver genes of interests. This methodology is important because genetic targeting of specific neurons allows one to draw a link between a neurons's anatomy (the regions it projects to) and its function (the information it encodes). This project will explore the engineering of novel tools that will significantly improve existing retrograde tracing techniques and thereby enable mapping behavioral functions to specific neuron types. The resulting tools will be made broadly available to the community to increase their impact and utility.<br /><br />As systems neuroscience is adopting tools from molecular biology there is an increasing appreciation for the importance of circuit-specific technologies, for instance targeting neuron-types defined by their projections using retrograde viral strategies for anatomical and genetic labeling. These tools have been critical for cell-type specific recordings using genetic activity indicators, or control using optogenetic actuators. Nevertheless, the efficiency and variable tropism (i.e. inability to target all cell types) of existing retrograde viruses presents a challenge for these experimental approaches. To overcome this challenge, two methods are proposed to generate reagents that will provide a non-toxic profile while maximizing efficient labeling of the targeted population. The methods will exploit well-understood molecular mechanisms for viral internalization to overcome tropisms, as well as classic tracers improved using a novel protein ligation technique. These reagents will be suitable for precise and robust anatomical tracing, for induction of opto- and chemicogenetic actuators. Therefore we expect that these improved reagents will allow for more efficient and less variable projection-based targeting of neurons with molecular cargo and facilitate new types of circuit-based mapping experiments.","FID":173}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Columbia University","Title":"The Digital Fly Brain","City":"New York","State":"NY","Abstract":"Several highly ambitious, large-scale, billion-pound research projects that aim to understand the human brain are currently under way. In Europe, The Human Brain Project is focused on accelerating brain research by integrating data available from a multitude of disparate research projects through the development of a multi-scale, multi-level model of the human brain - the 100 billion neurons modelling and simulation challenge. In the US, The Brain Initiative aims to reconstruct the full record of neural activity across complete neural circuits - the 100 billion neurons recording challenge. These are clearly huge, but worthy challenges that can benefit from an understanding of the principles of neural computation of much smaller yet sufficiently complex brains. The fruit fly brain has become one of the most popular model organisms to study neural computation and for relating brain structure to function. Many of the genes and proteins expressed in the mammalian brain are also conserved in the genome of the fruit fly. Remarkably, the fruit fly is capable of a host of complex nonreactive behaviors that are governed by a brain containing only ~100,000 neurons. The relationship between the fly's brain and its behaviors can be experimentally probed using a powerful toolkit of genetic techniques for manipulation of the fly's neural circuitry. Novel experimental methods for precise recordings of the fly's neuronal responses to stimuli and for mapping neurons and synapses in Drosophila nervous system have provided access to an immense amount of valuable data regarding the fly's neural connectivity map and its processing of sensory stimuli. These features coupled with the growing ethical and economic pressures to reduce the use of mammals in research, explain the growing interest in Drosophila-based brain models, not only to understand sensing, perception and neural computation, but also to gain mechanistic insights that may inform our efforts to address neurodegenerative diseases, such as Alzheimer's disease, in humans. <br /><br />This project aims to design, implement and experimentally evaluate a potentially transformative open-source fly brain simulation platform capable of simulating ~135,000 neurons that make up the adult Drosophila brain. This computational infrastructure will be based on the recently established Graphic Processor Units (GPU)-enabled Neurokernel software platform. The modular simulation platform will integrate all knowledge about the Drosophila brain as a set of interconnected simulation modules which describe the operation of about 41 Local Processing Units (LPUs), six hubs and their interconnections, partly elucidated by detailed EM imaging studies. The simulation platform will be used to develop and validate a first draft model that incorporates the most advanced biophysical and/or functional models of the neurons and the latest published synaptic connections maps. The main focus will be on developing detailed models of the early visual system (retina, lamina, medulla) and of the early olfactory system (OSNs, antennal lobe, mushroom body, lateral horn). These models will integrate complete models of the visual and olfactory systems. The brain simulation platform will enable for the first time the isolated and integrated emulation of fly brain model neural circuits and their connectivity patterns (e.g., sensory and locomotion systems) and other parts of the fly's nervous system on clusters of GPUs. Using the Neurokernel simulation platform it will be possible to generate data sufficiently fast to enable researchers to compare and tune the input-output characteristics of virtual neurons on-line, while the experiment is running.","FID":174}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Columbia University","Title":"BIGDATA: Collaborative Research: IA: Hardware and Software for Spike Detection and Sorting in Massively Parallel Electrophysiological Recording Systems for the Brain","City":"New York","State":"NY","Abstract":"Understanding how the brain works is arguably one of the most significant scientific challenges of our time and the focus of the BRAIN initiative. It is widely believed that neural circuit function is emergent, the result of complex interactions between constituents with individual neurons forming synaptic connections with thousands of other neurons. Mapping of these complex circuits has been virtually impossible because of the reliance on electrophysiological recordings which sample these networks extremely sparsely. These tools for extracellular spike recordings are only able to simultaneously record from several tens to a few hundred neurons. Raw signals from these recording electrodes are first filtered to remove out-of-band signals. Putative spike events are then detected and extracted. Finally, these snippets of time-series event are sorted, typically on the basis of waveform shapes, into clusters. Even at the very modest bandwidths for these systems, computing systems struggle to save the data and process the resulting data sets. Scalability of these measurement techniques by many orders of magnitude in recording density and channels will be essential to future progress in understanding neuron circuits.<br /><br />This project is exploiting emerging electrophysiological recording systems in which the electrode (and channel) count is increased by almost three orders of magnitude over conventional systems with data bandwidths exceeding 1GB/sec. To handle these data bandwidths and resulting data volumes and deliver scalability, this project will develop dedicated hardware and associated algorithms for spike detection and sorting that allow these tasks to be performed in real-time in close proximity to the recording system. Compression by more than three orders of magnitude is possible by these means by taking advantage of the special spatiotemporal local structure in these data sets; by exploiting strong prior information about the spiking signal and reducing the dimensionality of the problem accordingly; and by adapting and extending modern scalable nonparametric Bayesian inference methods. In addition to providing important new tools for neuroscience, the tools developed here for scalable real-time event detection and annotation have broad applicability to other spatiotemporal data sets (or more generally, any data set comprising multiple streams of data, in which the streams could involve different data modalities) in which objects of interest are spatially and temporally localized with fixed spatial footprints. Examples abound in cell and molecular biology, particle and solid-state physics, financial monitoring, monitoring of power networks, and sensor networks.","FID":175}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Cuny City College","Title":"CRCNS: Targeted Stimulations in Brain Network of Networks","City":"New York","State":"NY","Abstract":"The goal of this project is to investigate the signature of mental states, using the induction of transitions among states as an experimental strategy. The work is driven by a novel network theory -- Network of Networks (NoN) -- that emphasizes the importance of weak links. The project will identify a new network paradigm with the concomitant identification of network markers and computations that confer specificity and robustness to information transmission and gating between different processing modules. The prospective interventions are designed to provide strong empirical constraints on theories of brain network structure beyond the specific NoN hypothesis tested here, including alternate network models, e.g \"scale-free\" and \"rich-club,\" in order to obtain falsifiable predictions for the prospective interventions. The results can also be readily applied to other systems ranging from metabolic, protein and genetic networks to social networks and the Internet.<br /><br />The present study will test specific predictions of network theory with regards to the correlation structure of in-vivo functional magnetic resonance (fMRI) and local field potential (LFP) recordings. The investigators will determine network structure and location of key nodes in the brain network topology by analyzing the structural connectivity based on Connectome data from rodents combined with functional connectivity. The proposed NoN framework will reveal the location of such key nodes -- \"superspreaders\" and \"superinhibitors\" -- and make predictions on cascading neural activity, robustness and vulnerability of the brain network.","FID":176}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Columbia University","Title":"RI: Medium: Assessing Speaker and Teacher Effectiveness through Gestural Analysis, EEG Recordings, and Eye Tracking","City":"New York","State":"NY","Abstract":"This project helps speakers and teachers to measure and improve their impact on their audiences. It uses visual observations of body, head, and hand gestures of the communicator, plus recordings of brain activity and eye movements of the audience. Together, these determine which sections of a presentation elicit the most audience engagement. The project is developing new methods to capture and calibrate electroencephalogram and eye-tracking data from listeners and from students. It is determining new ways to relate this subject information to what a speaker or teacher can be seen to be doing while developing an argument or reviewing a concept. The project produces analyses of when and how the communicator is most effective. This system is being ported to the Columbia Video Network distance education facility, for their use in improving the online delivery of Columbia University Master's level technical courses. This project continues a research effort that has involved women, minorities, disabled students, and undergrads.<br /><br />This research investigates the degree to which certain speaker gestures can convey significant information that are correlated to audience engagement, in speeches and in classroom lectures. The project develops and validates a catalog of gestural attributes derived from pose and movements of body, head, and hand, and automatically extracts these attributes from videos. It demonstrates correlations between gesture attributes and an objective method of measuring audience engagement: electroencephalography (EEG). The project leverages a multi-disciplinary approach, with neural engineers and computer/media scientists collaborating to build a system that identifies and tracks physiological measures of engagement, and relates these to features in the video as well as information content. It records subjects' high-density EEG, and tracks their eyes and pupillary responses while they are watching video lectures. It uses machine learning, specifically novel methods which expand upon canonical correlation analysis, to relate inter- and intra-subject correlations, between the physiological changes and the gestural features derived from the video by using enhanced computer vision techniques. These measures are further integrated with pupillary measures, which have been shown to correlate with arousal, as well as with gaze measures, which are indicative of attention. The project is producing an analysis of body, head, and hand gestures useful in persuasion and in education, and a catalog of their influence on engagement and speaker effectiveness.","FID":177}},{"geometry":{"x":-8476687.3564,"y":5319628.473399997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Syracuse University","Title":"TWC: Small: Collaborative: Spoof-Resistant Smartphone Authentication using Cooperating Wearables","City":"Syracuse","State":"NY","Abstract":"This research is developing methods that leverage a multitude of sensors embedded in hand-held and wearable devices (e.g., smart watches, smart glasses and brain-computer interfaces) for strong user authentication to smart phones. The current point-of-entry solutions, largely based on weak static credentials, such as passwords or PINs for authentication to smart phones are not sufficient because once such credentials are compromised (which is very likely given the many vulnerabilities of passwords), the attacker may gain unfettered access to the smart phone. In this light, it becomes necessary to constantly protect the smart phone even after the attacker has already bypassed the point-of-entry authentication functionality. This research aims to address this problem by developing methods through which cues extracted from one or more wearable devices will be used in conjunction with cues extracted from the phone itself to continuously and unobtrusively verify the authenticity of the user. In addition to advancing knowledge on how wearable devices can help improve smart phone security, the research will have a number of other broader impacts including, mentoring of undergraduate students, outreach to high school and K-12 students and minority populations, and technology transfer by collaborating with manufacturers and industrial consortia.<br /><br />The principal argument underlying this research is that, given the rise of sensor-equipped and wearable computing, a wide array of identifying cues might be available in many circumstances and can therefore be leveraged to build user-friendly and spoof-resistant smart phone authentication systems. The overarching approach is to not only capture explicit user interactions (based on touch screen sensors) when applicable, but also capture implicit user interactions based on a conglomeration of a multitude of smart phone on-board sensors as well as wearable device sensors. The on-board sensors are inertial (motion and orientation) sensors residing on the smart phone itself and measure users' implicit interactions with the phone, specifically, phone movements, tilts and orientations. The wearable sensors, in contrast, are inertial and neuro-physiological sensors residing on \"collaborating\" wearable devices, \"paired\" with the smart phone, and measure user's interactions with those devices, specifically, movement dynamics associated with different body parts, and neuro-physiological patterns. The project is studying how the use of such multi-faceted cues can yield a smart phone authentication system that is robust against accidental errors as well as deliberate spoofing attacks.","FID":178}},{"geometry":{"x":-8450413.7158,"y":5175774.661399998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Suny At Binghamton","Title":"Biosensor Data Fusion for Real-Time Monitoring of Global Neurophysiological Function","City":"Binghamton","State":"NY","Abstract":"Real-time detection of acute changes in neurophysiological state, such as epileptic seizures, lapses in cognitive ability, acute stress, etc., can ultimately serve to prevent accidents in high-risk occupations that require unwavering focus. Such professions include hazardous cargo trucking, heavy machinery operation, security and defense, air traffic control, etc. Indeed, technology for acquiring rich biosensor data streams that capture brain function, e.g., electroencephalography, are becoming increasingly portable and noninvasive. These developments present an opportunity for implementing not only real-time monitoring, but also providing pre-emptive alerts (e.g., smart phone displays), which can be used to indicate degradation in physiological states. This research has direct applications in biomedical settings - for instance, epilepsy, is one of the most common neurological disorders afflicting over 50 million people worldwide, including 3 million people in the U.S. In about 25 percent of these patients, epileptic seizures are not controlled using available medications. Being able to detect (or predict) the onset of epileptic seizures would significantly enhance the patient's quality of life. In a proof-of-concept study, the novel analytical approaches by the research team detected the onset of epileptic seizures within 2.5 seconds. In contrast, existing approaches have a detection delay exceeding 7 seconds. From a broader perspective, the findings of this research can transform the status quo in real-time monitoring of neurophysiological function. The multidisciplinary research team will strive to provide state-of-the-art research and training opportunities for a diverse group of students that bridges the gap from engineering to the life and brain sciences. <br /><br />The research team will develop a sensor data fusion approach based on graph theoretic topological mapping to combine data acquired from multiple biosensors for neurophysiological change point detection. Unlike existing approaches, which rely on complex signal pre-processing, the graph theoretic approach eschews these computationally demanding steps and is therefore more viable in a practical setting. The research team will exploit this framework using a data library of high-resolution neurophysiological recordings acquired from end users in realistic settings that induce shifts in global functional states (e.g., acute stress, cognitive exhaustion, and fatigue and so on). The research team will integrate automated decision-making approaches in the overall schema to synthesize the information and provide easily interpretable feedback to the end user (e.g., displays on a smart device). Furthermore, the PIs will customize biosensors to accommodate the patient's lifestyle.","FID":179}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Rockefeller University","Title":"NCS-FO: A circuit theory of cortical function","City":"New York","State":"NY","Abstract":"This project aims to develop and test a new conceptual framework for understanding brain function, and informing biologically based artificial intelligence systems. The underlying theory holds that the properties of any neuron and any cortical area are not fixed but undergo state changes with changing perceptual task, expectation and attention. Because of the multiple routes by which this top-down information can be conveyed, each neuron is essentially a microcosm of the brain as a whole. <br /><br />In this framework, a neuron is viewed as an adaptive processor rather than merely a link in a labeled line, taking on functions that are required for performing the current task. The theory accounts for cortical function at the circuit level. Through an interaction between feedback and intrinsic connections neurons select inputs that are relevant to a task and suppress inputs that are irrelevant. The experiments will combine visual psychophysics, fMRI, large scale high density electrode array recordings and optogenetic manipulation. These techniques will be used to measure changes in effective connectivity between cortical areas and the relationship between effective connectivity and the information represented by neurons at different recording sites as animals perform different visual recognition tasks. Computational models will be developed to account for how task-dependent gating of connections can be achieved and will reproduce the functional dynamics observed experimentally. Though the experiments will focus on the visual modality, the findings from the work will formulate a general theory of brain function that is broadly applicable to the brain as a whole.","FID":180}},{"geometry":{"x":-8141898.2531,"y":4999492.6976,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Suny At Stony Brook","Title":"NCS-FO: Collaborative Research: Individual variability in human brain connectivity, modeled using multi-scale dynamics under energy constraints","City":"Stony Brook","State":"NY","Abstract":"Recent years have witnessed an explosion of interest in human brain connectivity and its relationship to brain-based disease. Functional connectivity analyses in neuroimaging have taken three general forms: cross-correlations, weighting of directed connections, and graph-theoretic approaches. Graph-theoretic measures, in particular, provide valuable insights into network features at the time of imaging. Yet, they cannot identify how the brain came to have those features, nor can they inform estimation of future network evolution. Neurological and psychiatric illnesses tend to have degenerative or oscillatory time-courses that range over decades; thus, network evolution will be critical to understanding why two individuals with the same diagnosis show markedly distinct developmental onsets and prognoses. <br /><br />At the most fundamental level, clinical neuroscience currently lacks the tools for probing how biological constraints imposed upon synapses impact functional connectivity patterns. These constraints include, among others: limited energy resources as per the aggregate energy conversion rate of a finite number of mitochondria, the need to balance excitatory and inhibitory neurotransmitters in order to maintain homeostasis, and neural repair mechanisms (e.g., inflammation, MMP-9). Our long-range goal is to develop these tools, focusing first upon energy constraints across synaptic-hemodynamic scales, for three strategic reasons. 1) Glycemic load is implicated in many neurological diseases, including epilepsy, brain cancer, and dementia. 2) Energy utilization is easy to manipulate experimentally through diet, and to quantify via CO-2 monitoring, with protocols that permit translation to/from animal models for multi-scale modeling. 3) Recent findings link neural connectivity to metabolic expenditure. In the short-term, we focus upon establishing feasibility for three critical principles in preparation for the proposed work. First, we will conduct a pilot neuroimaging study (36 scans; N=12, under three conditions) to establish that our proposed experimental manipulation of energy supply and demand provokes reorganization of brain networks. Second, we aim to bridge scales: to demonstrate how agent-based simulations of point-neurons can incorporate network structure imposed at the level of human neuroimaging, and evolve as a function of changing inputs (energy supply, demand). Third, we propose to develop/adapt methods required to mathematically characterize dynamic networks for both fMRI data and simulations. This fundamental work will position us to conduct future research on modeling of metabolic processes as a function of synapses, glia, and mitochondria, and to use these simulations to predict individual variability of fMRI results as a function of neural energy consumption.","FID":181}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Joan And Sanford I. Weill Medical College Of Cornell University","Title":"Collaborative Research: Olfactory Navigation: Dynamic Computing in the Natural Environment","City":"New York","State":"NY","Abstract":"This project was developed at an NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Physics of Living Systems program in the Physics Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Chemistry of Life Processes program in the Chemistry Division, and the Neural Systems Cluster in the Division of Integrative Organismal Systems. The project is a synergistic combination of laboratory experiments and computer modeling that will lead to better understanding of how animals use the sense of smell to navigate in the real world. Almost universally, from flies to mice to dogs, animals use odors to find critical resources, such as food, shelter, and mates. To date, no engineered device can replicate this function and understanding the code used by the brain will lead to many novel applications. Cracking codes, from neural codes to the Enigma code of WWII, is aided by a deep understanding of the content of messages that are being transmitted and how they will be used by their intended receivers. To crack the olfactory code, the team will focus on how odors move in landscapes, how animals extract spatial and temporal cues from odor landscapes, and how they use movement for enhancing these cues while progressing towards their targets. The proposed work encompasses physical measurement of odor plumes, behavioral measurement of animals' paths through olfactory environments, electrophysiological and optical measurement of neural activity during olfactory navigation, perturbations of the environment via virtual reality and of neuronal hardware via genetics, and multilevel mathematical modeling. The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. The project's results may lead to improved methods for the detection of explosives, new olfactory robots to replace trained animals, and new theoretically-grounded advances in robotic control. The project will inform the development of technologies that interfere with the ability of flying insects (including disease vectors and crop pests) to locate their odor target, thus opening a new door for developing 'green' technologies to solve problems that are of global economic and humanitarian importance.<br /><br />This proposal is a synergistic combination of laboratory experiments and computational modeling that will probe how animals use olfaction to navigate in their environment. Specifically, this effort seeks to solve the difficult problem of olfactory navigation through the following aims: (i) Generate and quantify standardized, naturalistic odor environments that can be used to perform empirical and theoretical tests of navigation strategies; (ii) Determine phenomenological algorithms for odor-guided navigation through behavioral experiments in diverse animal species; (iii) Determine how odor cues for navigation are encoded and used in the nervous system by recording neuronal data and simulating putative neural circuits that implement these processes; (iv) Manipulate olfactory environments and neural circuitry, to evaluate model robustness. In contrast to previous attempts to understand olfactory navigation, the present strategy emphasizes mechanisms that are biologically feasible and explores the wide range of temporal and spatial scales in which animals successfully navigate. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering (fluid mechanics, electronic olfaction, and robotics) and biology (neuroscience, ecology and evolution).","FID":182}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"New York University Medical Center","Title":"Collaborative Research: Olfactory Navigation: Dynamic Computing in the Natural Environment","City":"New York","State":"NY","Abstract":"This project was developed at an NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Physics of Living Systems program in the Physics Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Chemistry of Life Processes program in the Chemistry Division, and the Neural Systems Cluster in the Division of Integrative Organismal Systems. The project is a synergistic combination of laboratory experiments and computer modeling that will lead to better understanding of how animals use the sense of smell to navigate in the real world. Almost universally, from flies to mice to dogs, animals use odors to find critical resources, such as food, shelter, and mates. To date, no engineered device can replicate this function and understanding the code used by the brain will lead to many novel applications. Cracking codes, from neural codes to the Enigma code of WWII, is aided by a deep understanding of the content of messages that are being transmitted and how they will be used by their intended receivers. To crack the olfactory code, the team will focus on how odors move in landscapes, how animals extract spatial and temporal cues from odor landscapes, and how they use movement for enhancing these cues while progressing towards their targets. The proposed work encompasses physical measurement of odor plumes, behavioral measurement of animals' paths through olfactory environments, electrophysiological and optical measurement of neural activity during olfactory navigation, perturbations of the environment via virtual reality and of neuronal hardware via genetics, and multilevel mathematical modeling. The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. The project's results may lead to improved methods for the detection of explosives, new olfactory robots to replace trained animals, and new theoretically-grounded advances in robotic control. The project will inform the development of technologies that interfere with the ability of flying insects (including disease vectors and crop pests) to locate their odor target, thus opening a new door for developing 'green' technologies to solve problems that are of global economic and humanitarian importance.<br /><br />This proposal is a synergistic combination of laboratory experiments and computational modeling that will probe how animals use olfaction to navigate in their environment. Specifically, this effort seeks to solve the difficult problem of olfactory navigation through the following aims: (i) Generate and quantify standardized, naturalistic odor environments that can be used to perform empirical and theoretical tests of navigation strategies; (ii) Determine phenomenological algorithms for odor-guided navigation through behavioral experiments in diverse animal species; (iii) Determine how odor cues for navigation are encoded and used in the nervous system by recording neuronal data and simulating putative neural circuits that implement these processes; (iv) Manipulate olfactory environments and neural circuitry, to evaluate model robustness. In contrast to previous attempts to understand olfactory navigation, the present strategy emphasizes mechanisms that are biologically feasible and explores the wide range of temporal and spatial scales in which animals successfully navigate. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering (fluid mechanics, electronic olfaction, and robotics) and biology (neuroscience, ecology and evolution).","FID":183}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Rockefeller University","Title":"Geometry, Genetics and Development","City":"New York","State":"NY","Abstract":"Stem cells (SC) have the potential to revolutionize medicine by facilitating the regeneration or replacement of damaged tissues. Crucial for the use of hSC in medicine is control over inter-cell communication, since those pathways are the ones responsible for making patterns and integrating the fate of a cell with its environment. In this project the PI will develop quantitative models of how spatial patterns arise and evolve in populations of stem cells. The predictions of these models will be tested experimentally. The understanding of the spatial patterns formed by stem cells will be used to understand cell-cell communication and how cells interact with their environment that is very important in biology, medicine, and bioengineering.<br /><br />Recently an assay was developed for differentiating hSC on micropatterned surfaces, that generates the precursors to ectoderm, mesoderm, endoderm, etc. tissues in a spatial arrangement that recapitulates the embryo. This assay permits easy time lapse imaging of stem colonies while the cells signal to each other, move, and acquire distinct patterns of gene expression. Cells can be engineered to produce specific signals on demand and then mixed with naive cells and the emergent patterns followed over time. The relevant signals are generally present at too low a level to be observed directly, so a complex modeling procedure is needed to infer them from the response of the receiving cells. Critical for the success of any modeling in this area are succinct representations for the activity of the hundreds of genes that pattern an embryo. Modern mathematics provides the template for such models, and a separate project will test their application to the development of an organ in the nematode C.elegans. Through a collaboration, this project has access to many hSC lines with fluorescent tags on the genes that mediate cell signaling, and Physicists learn how to derive such lines themselves. Image processing systems developed in house are integrated with experiments to ask whether quantitative and predictive models formulated with only a few variables and guided by geometry are feasible. The goal is an algorithm to select among the infinite combinations of signaling molecules, their concentrations, and the time and duration of their application, the most efficient way to derive any desired cell or tissue from pluripotent cells.","FID":184}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"New York University","Title":"CAREER: Solving Olfactory Circuits in the Drosophila Larva","City":"New York","State":"NY","Abstract":"The sense of smell is important to humans? daily lives, and its loss is often a precursor to neurodegenerative diseases, but studying the human olfactory system directly, like all studies of human neural function, faces challenges due to the brain?s complexity, large number of neurons, and ethical and technical obstacles. Studying the larva's simplified olfactory system will advance understanding of the basic principles of human sense of smell. Insects are mportant disease vectors and agricultural pests who rely extensively on smells to locate food, hosts, and mates, so this work will have important applications in pest control. Undergraduates and high school students, especially from underrepresented groups, will be actively involved in the research. An additional component of this project is outreach to local elementary students, especially the creation of a program to engage students in tinkering and construction. <br /><br />How do brains make decisions based on noisy and often conflicting sensory input? Why does the same input elicit variable behaviors, even in the simplest organisms? This project aims to use the fruit fly larva's sense of smell as a model to explore these questions by studying the olfactory system of the Drosophila larva. A given odor stimulates or inhibits a set of odor receptor neurons, yet on the basis of this pattern of stimulation, organisms from flies to humans recognize and classify odors rapidly and reliably. The PI will image the responses of odorant receptor neurons in the larva's dorsal organ (its \"nose\") to understand how olfactory information is first presented to the brain, taking advantage of the genetic tools available in Drosophila, the larva's transparency, and custom built apparatus developed in the PI's lab. A second goal of this project is to develop the technology necessary to take full advantage of the larva as a model for decoding the neural circuitry of olfaction. To move towards or away from an odor, the larva uses sensory input to drive motor output. In this process, it modulates a number of behaviors, e.g. moving forward, stopping, and sweeping the head to one side or the other. The rules by which the larva changes its motor output in response to sensory input in order to move towards a goal represent a navigational strategy. Using light activated ion channels the PI will evoke activity directly in the sensory neurons in order to measure the computations involved in transforming temporal variations in sensory input into directed motor output. The promise of the larva, a small crawling animal with a transparent skin, is that the neural activity in freely behaving animals can be visualized. In practice, we do not have a microscope capable of keeping up with a moving animal. The project will develop a microscope that can track individual neurons in a moving larva making possible to \"read the larva's mind\" as it goes about its business, allowing us to link together sensory input, neural activity, and evoked behavior in order to understand the function of neural circuits. <br /><br />This project is being jointly supported by the Physics of Living Systems program in the Division of Physics the Neural Systems Cluster in the Division of Integrated Orgamismal System, and the Emerging Frontiers program in the Biological Sciences Directorate.","FID":185}},{"geometry":{"x":-8476687.3564,"y":5319628.473399997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Syracuse University","Title":"Near the onset of rigidity in living and nonliving matter","City":"Syracuse","State":"NY","Abstract":"NONTECHNICAL SUMMARY <br />Have you ever played a game of \"Pick up Sticks\" and wondered how an entire structure of randomly arranged sticks can collapse with the removal of just one stick? And have you ever wondered how a skin cell changes shape to crawl towards a wound to heal it? The notion of the onset of mechanical rigidity in both living and nonliving matter will help answer both of these seemingly disparate questions. <br /><br />To explore the emergence (and destruction) of mechanical rigidity in nonliving matter, the proposed modeling will be based on a collection of frictionless, repulsive soft spheres; while in living matter, it will utilize a disordered spring network. The PI's group will test both models by investigating what properties - friction, particle/filament shape, type of crosslinking between filaments, local mechanical stability - affect the nature of the rigidity transition. These models will be used to describe mechanical stability of two- and three-dimensional systems including granular systems, filamentous cytoskeletal networks, and biological tissue in the brain. The proposed work, therefore, extends the reach of materials science to living systems to help drive the emerging field of quantitative biology. <br /><br />The results of the proposed research will be used for development of a new course material on rigidity in both living and nonliving systems at undergraduate and graduate levels. The proposed collaborations with Syracuse Museum of Science and Technology and the YWCA will educate the public about the intrigue of soft matter. The PI will use her knowledge and experience to recruit women to the physical sciences by presenting scientific advances used to decouple the biological clock and the tenure clock to senior graduate students and post-docs. <br /><br /><br />TECHNICAL SUMMARY <br />How does a collection of randomly packed frictional particles at the threshold of mechanical rigidity destabilize with the deletion of just one contact? And how does a collection of cytoskeletal filaments attain mechanical rigidity to extend the reach of a cell? In nonliving matter, the model will be based on a collection of frictionless, repulsive soft spheres; while in living matter, it will utilize a disordered spring network. The PI's group will test the robustness of both models by investigating what properties - friction, particle/filament shape, type of crosslinking between filaments, local mechanical stability - affect the nature of the rigidity transition. To test for this robustness in nonliving systems, the local properties of mechanical stability at the onset of rigidity for frictionless, repulsive soft discs in two dimensions will be studied by using concept of jamming graph. Armed with the information of constraint counting, geometry, and force-balance, the PI's group will develop a model for the onset of rigidity in frictionless, particulate matter. <br /><br />The emergence (and destruction) of rigidity abounds in living matter as well. The actin filament cytoskeletal network adjusts its morphology to support the cell structurally. The proposed research will narrow the existing theoretical gap between morphology and mechanics by building disordered spring network models that encode more of the network morphology, such as anisotropy and angle-constraining crosslinks, to determine which aspects are more relevant to the onset of rigidity than others. Moreover, quantitative modeling of biological tissue in the brain will be developed using vertex models, which are related to disordered spring networks. The PI's group will investigate the interplay between morphology and mechanics to determine how glial cells structurally support bundles of neurons. <br /><br />The results of the proposed research will be used for development of a new course material on rigidity in both living and nonliving systems at undergraduate and graduate levels. The proposed collaborations with Syracuse Museum of Science and Technology and the YWCA will educate the public about the intrigue of soft matter. The PI will be involved in the recruitment of women to the physical sciences by presenting scientific advances used to decouple the biological clock and the tenure clock to senior graduate students and post-docs.","FID":186}},{"geometry":{"x":-8780709.6401,"y":5294551.337899998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Suny At Buffalo","Title":"International Symposium on Quantum Fluids and Solids-QFS2015","City":"Buffalo","State":"NY","Abstract":"Non-Technical Abstract<br /><br />This award supports the International Symposium on Quantum Fluids and Solids-QFS2015. This conference will bring together leading scientists from a variety of fields in quantum fluids and solids in a collegial atmosphere that supports open discussion to discuss issues at the cutting edge of soft matter physics. This meeting will focus on two topics at the forefront of quantum fluids and solids which include liquid and solid 4He, 3He and 3He-4He mixtures, hydrogen, trapped atomic gases and optical lattices, magnetism and superconductivity, condensed matter systems in the quantum limit, model systems in cosmology and high energy physics and novel experimental low temperature techniques. In addition, this conference will include a number of tutorials for young researchers which will introduce them to senior workers in the field and provide an opportunity to build informal networks with their peers.","FID":187}},{"geometry":{"x":-8238434.544399999,"y":4970328.659100004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Columbia University","Title":"Coulomb drag in ultra-clean and strongly interacting van der Waals materials: toward exciton condensation","City":"New York","State":"NY","Abstract":"Non-technical Abstract<br />The aim of this project is to experimentally study the interactions between electrons in two coupled two-dimensional (2D) sheets. When the 2D layers are sufficiently close, interlayer Coulomb interactions result in momentum transfer so that electrons moving in one layer cause those in the second sheet to move in response, a phenomenon known as Coulomb drag. This work will study layered heterostructures of atomically thin materials -- including graphene and insulating boron nitride --to achieve atomic control over the spacing between the conducting layers. This will allow the exploration of Coulomb drag in the strong-coupling limit, and in high-mobility devices where electrical transport is ballistic. These structures are made possible by techniques developed by the Principle Investigators to fabricate ultraclean multi-layered heterostructures by mechanical layering of 2D materials. The primary effort will be a systematic characterization of the drag response in monolayer graphene versus temperature, density, layer separation, and magnetic field. Drag resistance together with inter-layer tunneling will additionally be used to pursue signatures of a theoretically-predicted exciton condensate phase in which spatially indirect excitons consisting of paired electrons and holes confined to separate layers condensed into a superfluid ground state. Careful studies of the Coulomb drag response provides a unique tool in which to study electron-electron interactions in mesoscopic systems, which is expected to have significant impact beyond the study of 2D systems, since electron-electron interactions underlie the rich and complex physics of correlated materials. If successful, this research could also enable revolutionary new low power electronic devices. The collaborative interdisciplinary work will provide training to a postdoctoral researcher as well as providing research experience to high school and junior level undergraduate students. Outreach efforts will focus on expanding long-term relationships with teachers at two affiliated public schools. <br /><br />Technical Abstract: <br />The aim of this project is to experimentally study Coulomb drag in high mobility double layer quantum wells fabricated from 2D materials, such as graphene and related van der Waals materials, in the strongly interacting limit of small interlayer separation. The primary goal will be a systematic characterization of the drag response in monolayer graphene heterostructures versus temperature, density and interlayer separation, under both zero and finite magnetic field, through transport measurements. Several outstanding questions will be addressed such as the anomalous density and temperature dependences reported previously, origin of the anomalous drag response at the double neutrality point, and the nature of the Hall response in the finite magnetic field regime. Drag resistance together with inter-layer tunneling will additionally be used to pursue signatures of the exciton condensate phase in two regimes (i) electron-hole graphene layers at zero magnetic field, and (ii) electron-electron graphene layers at half filled Landau levels in the quantum Hall regime. The experimental effort will include studies of heterostructures fabricated from bilayer graphene, and mono and few-layer transition metal dichalcogenides where the effect of a bandgap on the exciton binding has so far received no experimental attention. The Coulomb drag response in graphene is not well understood at the most basic level. Theoretical efforts to model this system have yielded conflicting results, none of which well match the few experimental studies that have been reported so far. In this regard the systematic study proposed here promises to lay important groundwork for future understanding of this system, and more generally to provide quantitative boundaries on key physical parameters necessary to accurately model electron transport in graphene such as the strength of electron screening versus density and the specific role of the dielectric environment.","FID":188}},{"geometry":{"x":-9093771.2359,"y":5087077.102600001,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Case Western Reserve University","Title":"HAPTIX","City":"Cleveland","State":"OH","Abstract":"Develop neural interfaces to improve fine motor control and restore sense of touch and proprioception for prosthetics users.","FID":189}},{"geometry":{"x":-9093771.2359,"y":5087077.102600001,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"The Cleveland Clinic Foundation","Title":"HAPTIX","City":"Cleveland","State":"OH","Abstract":"Develop neural interfaces to improve fine motor control and restore sense of touch and proprioception for prosthetics users.","FID":190}},{"geometry":{"x":-9372411.6851,"y":4831011.975100003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Wright State Applied Research Corporation","Title":"ElectRx","City":"Dayton","State":"OH","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":191}},{"geometry":{"x":-9093771.2359,"y":5087077.102600001,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Case Western Reserve University","Title":"SHF: Small: Bio-inspired ultra-broadband RF scene analysis","City":"Cleveland","State":"OH","Abstract":"The detection and analysis of structured signals in noisy and cluttered environments is a fundamental problem in areas ranging from radio communications to image processing and speech recognition. Biological sensory systems have been optimized by millions of years of evolution to solve this problem with exquisite precision and efficiency; man-made communication and signal processing systems do not achieve anywhere near the same level of performance or even share similar fundamental design principles. This project will try to bridge this gap by understanding the universal information processing principles used by the auditory system to analyze natural sounds, and then adapting them to analyze man-made radio frequency (RF) signals. In particular, it will focus on developing electronics and algorithms that emulate some of the amazing capabilities of the biological cochlea (inner ear) and auditory pathway. Graduate and undergraduate students including members of underrepresented groups will be trained as part of this research, thus enlarging the technologically trained workforce of the future.<br /><br />The bio-inspired approach of this project was motivated by two observations. Firstly, the process by which the auditory system, beginning with the cochlea, analyzes the fine time-frequency content of sounds is both extremely precise and also highly efficient from an algorithmic viewpoint. Secondly, audio and RF scenes are generated by similar physics (wave propagation, absorption, scattering, diffraction, and interference), even though the relevant velocities and time delays differ by a factor of about a million. Thus audio and RF scenes share many of the same characteristics, which makes it interesting to consider models of cochlear mechanics, signal transduction, and auditory coding that are scaled to operate at much higher frequencies. The first research goal is to build a single-chip cochlear model that analyzes RF signals in the GHz range and encodes frequency, amplitude, and phase information into parallel event-driven outputs that are analogous to auditory nerve fibers. The second goal is to allow higher-level properties, such as source locations and categories, to be efficiently extracted from input signals by developing a robust coding framework to create compressed representations of the cochlear outputs.","FID":192}},{"geometry":{"x":-9074103.494,"y":5024767.891500004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Akron","Title":"UNS: Design of Self-Assembling Peptides and their Conjugates as Amyloid Inhibitors","City":"Akron","State":"OH","Abstract":"PI: Zheng, Jie <br />Proposal Number: 1510099<br /><br />With the aging population, Alzheimer's (AD) and other age-related neurodegenerative diseases will continue to impact more lives with no cure available. Aggregation of amyloid-beta (Abeta) peptides is thought to contribute to dysfunction and loss of nerve cells in AD, so inhibition of Abeta aggregation holds considerable promise for the development of new therapies for AD. However, the existing inhibitors are not potent enough to be used as effective treatments. This project aims to develop a new class of peptide-nanoparticle inhibitors of improved biocompatibility, enzymatic resistance, and delivery properties against Abeta aggregation and toxicity. <br /><br />The objectives of this research are to (i) develop a new class of beta-sheet-forming self-assembling peptides (SAPs) and SAP-nanoparticle conjugates as amyloid-beta (Abeta) inhibitors with improved inhibitory ability, enzymatic degradation, and blood-brain barrier (BBB) permeability; and (ii) establish practical design principles that can consistently explain the sequence/structural dependence of functional interactions between SAP derivatives and Abeta peptides on amyloid aggregation, toxicity, and inhibition. To achieve these goals, de novo computation-aided design tools will be first developed to screen and identify SAPs from a large pool of peptide library, followed by experimental determination of the role of SAPs in Abeta inhibition and Abeta-induced cell toxicity. Then, SAP-nanoparticle conjugates will be developed to solve the issues of toxicity, degradation, and BBB permeation of SAPs by mutually controlling interfacial properties of both nanoparticles and conjugated peptides. Finally, a multiscale computational platform will be developed to integrate experimental and computational data to establish the sequence/structure-dependent relationship among aggregation property, membrane permeability, and cell toxicity of SAPs, and finally help to determine a set of rules for iterative design of SAP-derived inhibitors with tunable sequence and structural properties. The peptide inhibitors could be potentially useful for other neurodegenerative diseases, and peptide materials can also represent new protein-based self-assembled nano-/bio-materials for other biomedical applications. The interdisciplinary nature of the project provides a unique opportunity to train and educate all-level students to learn the concepts and tools in structural biology, bioinformatics, and engineering design. The knowledge derived from the proposal will be disseminated through undergraduate/graduate courses, high-impact journals, conference presentations, summer workshops/internships, and other outreach activities.","FID":193}},{"geometry":{"x":-9406956.5563,"y":4737029.201700002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Sense Diagnostics, Llc","Title":"SBIR Phase I: Novel Device for monitoring brain hemorrhage using radio waves.","City":"Cincinnati","State":"OH","Abstract":"The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the reduction of deaths and long-term disabilities in people suffering from bleeding in the brain caused by hemorrhagic stroke or traumatic brain injury. The presence of blood outside of the brain?s vessels and arteries creates a characteristic change in the radio signal used by the device. Currently, physicians are alerted to worsening bleeding only when a patient fails to respond appropriately to a clinical exam that consists of a series of questions and commands. The problem this presents is that by the time the exam uncovers the additional bleeding, much of the damage to the brain has already occurred. A large proportion of patients suffering either hemorrhagic stroke or TBI die or are left severely disabled. Each year over 70,000 people suffer hemorrhagic stroke, with over half of them dying. TBI is responsible for over 1 million emergency department visits, 225,000 hospital admissions and 50,000 deaths. Using radio waves to non-invasively detect brain bleeds will reduce the time it takes to start treatment, which will save lives, reduce disabilities and result in significant savings to the health care system.<br /><br />The proposed project will test the ability of the SENSE device to detect small amounts of blood (as little as 2 ml) in both a gelatin model that mimics the electrical properties of the human brain and in a well-established porcine intracranial hemorrhage model. The gelatin experiments will place blood at various locations throughout the model. The prototype device will scan both before and after blood insertion and the results will be compared to the known location and volume of blood to determine the ability of the device to accurately detect the blood. Once confirmed in gelatin models, the device will be tested in a porcine ICH model using an institution IACUC approved protocol to ensure humane treatment of the test animals. Under general anesthesia, a small volume of the pig?s own blood will be surgically infused into the brain. The device will scan the pig?s brain both before and after insertion of the blood. After the scans are complete,the animals will be euthanized. The brain will be frozen in liquid nitrogen and sectioned. The scan results will be compared to the sectioned brain to determine the device?s ability to accurately detect the location and volume of blood.","FID":194}},{"geometry":{"x":-9074103.494,"y":5024767.891500004,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Akron","Title":"Neurotechnologically inspired multilayered polymer electrolyte membranes to harness ion concentration gradient for energy restoration","City":"Akron","State":"OH","Abstract":"NON-TECHNICAL SUMMARY:<br /><br />The main concept of this project emerges from the neuronal circuits of the body as paradigms for novel types of solid-state batteries based on mechanisms operative in neurotransmission. The brain controls various functions of the body through the nervous system composed of neuronal networks. Neurons are excitable, individual cells making specific contacts with other surrounding neurons. Their signal-processing is empowered by ion osmosis, driven by ion concentration gradients across the cell membrane which regulates passage of selective ions via ionic channels. The concept of polymer-based solid lithium ion batteries to be explored in this project shares this common origin with neuronal networks, as it operates by harnessing ion concentration gradients across the proposed \"multilayered polymer electrolyte membranes\" (MLPEM) which contain different ion concentrations in each layer, thus generating an internal voltage. The proposed concentration-gradient approach to battery design is conceptually similar to the neuronal operation of an electric eel, whereby series of thousands of innervated and non-innervated cell membranes are capable of generating internal voltages of about 600 volts to fend off predators. Just as the neural network of the electric eel allows this voltage to be regenerated, the proposed MLPEM batteries could be rechargeable on their own. The working principle of the self-rechargeable battery in this project is that the mobile lithium cation will be transported to the cathode during discharging, but it will revert back to the anode during battery resting, thereby restoring the ion concentration gradient and hence a voltage. This project will explore these aspects by synthesizing and processing multilayered polymer electrolyte membranes allowing ionic concentration gradients, evaluate and attempt to optimize the ionic conductivity, the thermal and electrochemical stability, and the mechanical properties of the battery. If successful, this project may benefit society by leading to novel lightweight, shape-conformable, thermally and electrochemically stable, flame-retardant, self-rechargeable batteries. The project also includes integration of research and education through interdisciplinary training of students and outreach activities.<br /><br /><br />TECHNICAL SUMMARY:<br /><br />This project is inspired by the neuronal circuits of the body as paradigms for novel types of solid-state batteries based on mechanisms operative in neurotransmission, e.g. the generation of high voltages by electric eels followed by internal recharging. It focuses on five thrust areas: (1) Development of all-solid-state multilayered polymer electrolyte membranes (MLPEM) having specific chemical and electrochemical compatibility with electrodes for enhancing energy-storage capacity. MLPEM will be fabricated by stacking individual polymer electrolyte (PEM) layers having different ion populations by photopolymerizing network-precursor (poly(ethylene glycol) diacrylate)/solid plasticizer (succinonitrile)/ionic salt (lithium bis-trifluorosulfonylimide). The ion concentration gradient thus produced in MLPEM will create potential differences across the membrane interfaces, thereby affording self-rechargeability of the battery. (2) Fabrication of directionally aligned phase-separated domains having various concentration gradients via holographic photopolymerization-induced phase separation in multicomponent solid electrolytes containing plasticizer and modifiers as a means of creating networks of micro-electrolyte cells. (3) Synthesis of PEM additives such as amido-carbonyl carbamate and amido-carbamate to prevent uncontrolled solid electrolyte interface formation on electrodes. (4) Grafting of poly(ethylene glycol) diamine to multiwall carbon nanotube (MWCNT) followed by end-capped reaction with carbamate derivatives to improve interface compatibility of MLPEM with carbonaceous anode and concurrently increase in ionic conductivity. (5) Modification of MWCNT surface by grafting of lithiated PEG-chains and/or arborescent PEG to raise lithium ion storage capacity and provide separate pathways for electron and ion conductions. The network of lithiated arborescent hyperbranched PEG resembles a neuronal network structurally and functionally. The ion conductivity and mobility will be determined by AC impedance, solid-state NMR, and Raman spectroscopy. Electrochemical stability will be evaluated by means of cyclic voltammetry and galvanostatic charge/discharge cycling in half-cell configurations. By virtue of the self-restored potential difference between the electrodes afforded by the ion concentration gradient of MLPEM, the battery would be rechargeable in the rest state, thereby prolonging the battery life. The project includes integration of research and education through interdisciplinary training of students and outreach activities.","FID":195}},{"geometry":{"x":-9239823.5582,"y":4860420.686999999,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Ohio State University","Title":"NCS-FO: Collaborative Research: Understanding Individual Differences in Cognitive Performance: Joint Hierarchical Bayesian Modeling of Behavioral and Neuroimaging Data","City":"Columbus","State":"OH","Abstract":"Understanding the complex determinants of individual health and wellbeing is critical for the promotion and maintenance of a healthy world population. Wellbeing may be understood not only as the absence of physical and mental illness but also as the quality of life and optimal functioning of individuals. It is well known that individuals vary tremendously in terms of cognitive abilities and dispositions, as seen from performance on high-order cognitive tasks, decision-making preferences, and emotional competencies. However, the neural underpinnings of much of this variability are poorly understood: It is unclear how individual differences in brain structure and function across tasks and processes are linked to abilities and competencies. This project explores a mathematical and computational framework for investigating a large-sample neuroimaging and behavioral dataset in order to improve our understanding of individual differences in cognitive performance. An ultimate goal of the project is to predict individual cognitive performance in novel, real-world situations based on observed (past) behavioral and neuroimaging data and contribute to the understanding of cognitive health and wellbeing of individuals. The project will also offer many training opportunities for the next generation of scientists. <br /><br />The technical approach will build on and integrate recent advances in cognitive science, neuroscience, statistics, and machine learning. Statistical models will integrate data from both brain imaging and behavioral tests to generate predictions that otherwise may not be possible with a single source of data. The research will go beyond establishing and explaining individual differences to predicting individual cognitive performance in a variety of tasks.","FID":196}},{"geometry":{"x":-1.36561885162E7,"y":5702455.254199997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Oregon Health Sciences University","Title":"SUBNETS","City":"Portland","State":"OR","Abstract":"Develop new neural interfaces to measure how system disorders manifest in the brain and precisely deliver therapy in humans with neuropsychiatric and neurologic diseases","FID":197}},{"geometry":{"x":-1.36561885162E7,"y":5702455.254199997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Reed College","Title":"BRAIN STEM Workshop, Chicago, Illinois, October 14-17, 2015","City":"Portland","State":"OR","Abstract":"President Obama's BRAIN Initiative (BRAIN; Brain Research through Advancing Innovative Neurotechnologies) is directed at supporting projects that seek to advance understanding of normal brain function. A workshop to identify areas where faculty and students from primarily undergraduate institutions (PUI) can make unique contributions to the BRAIN Initiative will be held on October 14-17, 2015 in Chicago, IL. The central goal of the workshop is to enhance PUI involvement in the research challenges described in the Brain Initiative. Consonant with advancing the goals of the BRAIN Initiative, the workshop will focus on developing ways to further NSF's mission to prepare a scientifically literate workforce.<br /><br />A diverse group of twenty-four researchers from PUIs throughout the United States will be invited to participate in discussions of research, neurotechnology, computational approaches, and interdisciplinary training of undergraduates. The workshop will be held in Chicago, Illinois 3 days before the annual Society for Neuroscience (SFN) conference, also scheduled to be held in Chicago. Workshop participants will produce a report of their discussions, conclusions and recommendations aimed at increasing the participation of PUI faculty and their undergraduate research students in the BRAIN Initiative. The report will be made available to the public on the NSF website (http://www.nsf.gov/bio/pubs/reports/index.jsp ), and distributed to the scientific community through the Faculty for Undergraduate Neuroscience website (http://www.funfaculty.org/drupal/ ). The workshop outcomes will also be compiled into a self-running presentation for dissemination at local PUI consortia, academic conferences, and national meetings. It is anticipated that outcomes of the discussion at the workshop will be disseminated through conversations with researchers attending the SFN annual meeting.","FID":198}},{"geometry":{"x":-1.36561885162E7,"y":5702455.254199997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Oregon Health & Science University","Title":"Large-Scale Recording-Modulation - New Technologies","City":"Portland","State":"OR","Abstract":"A novel approach to examine slow synaptic transmission in vivo","FID":199}},{"geometry":{"x":-8905277.4498,"y":4929846.7337,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"University Of Pittsburgh","Title":"HAPTIX","City":"Pittsburgh","State":"PA","Abstract":"Develop neural interfaces to improve fine motor control and restore sense of touch and proprioception for prosthetics users.","FID":200}},{"geometry":{"x":-8905277.4498,"y":4929846.7337,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Carnegie Mellon University","Title":"ElectRx","City":"Pittsburgh","State":"PA","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":201}},{"geometry":{"x":-8667389.8724,"y":4982850.017800003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Pennsylvania State Univ University Park","Title":"Collaborative Research: Analysis of the Mammalian Olfactory Code","City":"University Park","State":"PA","Abstract":"This project was developed during a NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Chemistry of Life Processes program in the Chemistry Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Physics of Living Systems program in the Physics Division, the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Division of Biological Infrastructure, and the Division of Emerging Frontiers.<br /><br />The mammalian sense of smell is arguably the most complex sensory system in the animal kingdom. Hundreds of olfactory receptors are deployed to detect a vast array of chemicals with exquisite sensitivity in complex environments. This collaborative project combines biochemistry, neurobiology, genomics, mathematics and new technologies to understand how the mammalian olfactory system detects, encodes and extracts meaning from chemical stimuli. The goals of this project are to: (1) elucidate fundamental neural mechanisms for how chemical sensation turns into the perception of a smell; (2) produce a vast array of scientific resources to olfactory scientists; (3) provide valuable information for broader audiences, including for molecular evolution, chemical ecology, and flavor and fragrance communities; (4) establish new technologies and mathematical frameworks to study biological systems; and (5) facilitate applied chemical sensing technologies for environmental monitoring, food safety, and homeland security. The project also offers training opportunities from the high school to the postdoctoral trainee level, and educational opportunities and outreach through partnerships with local science museums as well as science learning centers and their media outlets.<br /><br />This project's efforts are organized around three aims that focus on how information about odor identity and odor valence (attractiveness/aversiveness) is encoded at the level of olfactory receptors (Aim 1); within the olfactory bulb, where odor information is first processed (Aim 2); and the cortical amygdala, where odor codes may integrate with other information streams (Aim 3). Completion of the project entails the development and use a broad array of innovative approaches that include mapping all human and mouse odorant receptors to the chemicals they bind, defining the innate valence of these chemicals using behavioral assays, mapping all odorant receptor projections to the olfactory bulb, functionally characterizing their neural representations in the olfactory bulb and cortical amygdala, and using novel mathematical approaches to understand the underlying structure of odor coding and olfactory neural circuits at the level of sensory neurons, olfactory bulb glomeruli, and amygdala. Progress towards each aim involves close collaborations between team members with diverse expertise, including molecular biology, behavioral neuroscience, in vivo functional imaging, and mathematical and theoretical analysis of complex datasets. The multidisciplinary strategy implemented here promises to lead to an integrated and comprehensive understanding of how mammals sense and make sense of their chemical environments.","FID":202}},{"geometry":{"x":-8367045.175899999,"y":4859010.612800002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Pennsylvania","Title":"US-French Research Proposal: Collaborative Research: Predicting Odorant-dependent and Independent Olfactory Neuron Activation Based on Receptor","City":"Philadelphia","State":"PA","Abstract":"Smell is a powerful sense that can trigger intense emotion, stereotyped behaviors and durable memories. The sense offers an extraordinary opportunity to connect atomic-level objects (odorant molecules and smell receptors in the nose) to neural responses. This project will predict which smell receptors in the nose are activated by a given odor. To accomplish this goal, the team of investigators will apply computational approaches to develop chemical structure-based receptor models and test these models using odor molecules interacting with olfactory receptors. The success of the project will enable the team to understand more precisely how the brain perceives the external environment. The results will also have widespread and diverse industrial applications, including rational design of new flavors and fragrances and development of new biosensors for detecting various chemicals. Furthermore, this project will make broader impacts in training and educating high school, undergraduate, and graduate students in various disciplines as well as in outreaching activities.<br /><br />The complexity of the odor molecules, the large number of the smell receptors and combinatorial activation of the receptors make understanding odor coding an enormous challenge. This collaborative proposal represents the first of its kind that combines computational approaches with experimental measurements at both the receptor and the neuron level. Affinity calculations between odorants and the receptors, as well as the receptors' activation, will be obtained by nanosecond-scale simulations. Atomic-level simulations, initially assessed by experiments, will predict which odors would activate the receptors of interest. Comparisons between experimental findings and computational predictions will lead to a comprehensive computational model that converges with experimental data. <br /><br />A companion project is being funded by the French National Research Agency (ANR).","FID":203}},{"geometry":{"x":-8667389.8724,"y":4982850.017800003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Pennsylvania State Univ University Park","Title":"Computational Prediction of Mechanical and Transport Response Evolution in Degrading Porous Scaffolds","City":"University Park","State":"PA","Abstract":"Restoring living tissue functionality via tissue engineering is crucial for transformative advances in medicine. Tissue engineering materials must be biocompatible and often biodegradable in a controlled manner. For example, severed peripheral nerves can regrow, but new projections must be properly nourished and guided via tissue scaffolds. Scaffolds must have the right morphology for cell growth, the right transport properties for nourishing cells, and the right mechanical properties to stay compliant and integral during degradation and tissue regeneration. Biodegradable scaffolds are appealing because they need not be surgically removed; but they are effective only if degradation is synchronized with nerve regrowth. This is but one of many examples illustrating the extraordinary challenges in tissue engineering. This award will yield a multi-scale approach based on physics, mathematics, polymer chemistry, and image analysis to predict and interrogate evolving transport and mechanical properties of porous polymeric scaffolds during programmed enzymatic degradation. The contribution of the project to the advancement of mechanics is a new methodology to model, and thus understand, the behavior of multi-functional materials with evolving microstructure like those in nerve tissue engineering. An educational component is included to attract underrepresented minorities to engineering via level-appropriate workshops on applications of mechanics in neuroscience, and by involving undergraduates in the creation of coursework for courses in brain biomechanics.<br /><br />Biodegradable tissue engineering systems are deformable chemically-reacting porous mixtures with complex fluid-structure interaction. The project integrates specific existing averaging techniques with an original fluid-structure interaction approach to determine the coupled mechanical and transport properties of degrading porous polymer networks subjected to large deformation and mechanical loadings. The model system of relevance to the project is crosslinked urethane-doped polyester, a promising scaffold material for nerve regeneration with highly controllable porosity. This material will be modeled as a random polymer network. Samples will be analyzed via electron microscopy to quantify the network's morphology. Microscopic-level transport and mechanical properties will be determined via a statistical characterization of the polymer network structure. This process will define microstructurally accurate representative volume elements whose evolution can then be analyzed via a novel finite element fluid-structure interaction-based homogenization procedure for evolving microstructure due to degradation. This numerical scheme will yield effective mechanical and transport properties at the mesoscale as a function of degradation. A crucial advancement in mechanics is the framing of the homogenization problem as a fluid-structure interaction problem, by extending the immersed finite element method (a state-of-the-art fluid-structure interaction computational approach) to account for fluid flow through bodies with evolving microstructure. The project includes experiments to validate predicted properties. Material samples and full-scale scaffold at different stages of degradation will be characterized in terms of morphology, elastic moduli, and diffusivity, and these properties compared to corresponding numerical estimates.","FID":204}},{"geometry":{"x":-8905277.4498,"y":4929846.7337,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Pittsburgh","Title":"Collaborative Research: Olfactory Navigation: Dynamic Computing in the Natural Environment","City":"Pittsburgh","State":"PA","Abstract":"This project was developed at an NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Physics of Living Systems program in the Physics Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Chemistry of Life Processes program in the Chemistry Division, and the Neural Systems Cluster in the Division of Integrative Organismal Systems. The project is a synergistic combination of laboratory experiments and computer modeling that will lead to better understanding of how animals use the sense of smell to navigate in the real world. Almost universally, from flies to mice to dogs, animals use odors to find critical resources, such as food, shelter, and mates. To date, no engineered device can replicate this function and understanding the code used by the brain will lead to many novel applications. Cracking codes, from neural codes to the Enigma code of WWII, is aided by a deep understanding of the content of messages that are being transmitted and how they will be used by their intended receivers. To crack the olfactory code, the team will focus on how odors move in landscapes, how animals extract spatial and temporal cues from odor landscapes, and how they use movement for enhancing these cues while progressing towards their targets. The proposed work encompasses physical measurement of odor plumes, behavioral measurement of animals' paths through olfactory environments, electrophysiological and optical measurement of neural activity during olfactory navigation, perturbations of the environment via virtual reality and of neuronal hardware via genetics, and multilevel mathematical modeling. The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. The project's results may lead to improved methods for the detection of explosives, new olfactory robots to replace trained animals, and new theoretically-grounded advances in robotic control. The project will inform the development of technologies that interfere with the ability of flying insects (including disease vectors and crop pests) to locate their odor target, thus opening a new door for developing 'green' technologies to solve problems that are of global economic and humanitarian importance.<br /><br />This proposal is a synergistic combination of laboratory experiments and computational modeling that will probe how animals use olfaction to navigate in their environment. Specifically, this effort seeks to solve the difficult problem of olfactory navigation through the following aims: (i) Generate and quantify standardized, naturalistic odor environments that can be used to perform empirical and theoretical tests of navigation strategies; (ii) Determine phenomenological algorithms for odor-guided navigation through behavioral experiments in diverse animal species; (iii) Determine how odor cues for navigation are encoded and used in the nervous system by recording neuronal data and simulating putative neural circuits that implement these processes; (iv) Manipulate olfactory environments and neural circuitry, to evaluate model robustness. In contrast to previous attempts to understand olfactory navigation, the present strategy emphasizes mechanisms that are biologically feasible and explores the wide range of temporal and spatial scales in which animals successfully navigate. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering (fluid mechanics, electronic olfaction, and robotics) and biology (neuroscience, ecology and evolution).","FID":205}},{"geometry":{"x":-8905277.4498,"y":4929846.7337,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Carnegie-Mellon University","Title":"CRCNS: Rhythm Generation and Propagation by a Pallidostrialtal Circuit of the Basal Ganglia","City":"Pittsburgh","State":"PA","Abstract":"In specialized brain areas called the basal ganglia, neurons generate certain rhythmic activity patterns during particular stages of motor processing. This rhythmicity becomes enhanced in disorders such as Parkinson's disease (PD), where pathological activity patterns include pronounced oscillations within certain frequency bands, increased synchrony, and phasic bursting. These patterns of amplified rhythmicity are thought to compromise functionality of basal ganglia networks and to contribute to motor impairments. The overarching goal of this work is to understand how cellular and synaptic changes that occur in PD render neural circuits in the basal ganglia more susceptible to rhythmic activity in disease. Specifically, this research will focus on an understudied neural circuit that is well positioned to influence rhythmicity throughout the basal ganglia and will help to identify potential cellular targets to disrupt pathological network activity in disease. A combination of in vivo and in vitro physiological approaches together with computational model development, simulation, and analysis will be used to identify biological features of this circuit that can generate and maintain rhythmicity and to explain how this network contributes to runaway rhythmicity in PD. <br /><br />The external segment of the globus pallidus (GPe) is a central nucleus within the basal ganglia that has been strongly implicated in the onset and maintenance of rhythmic activity. Under normal conditions, neurons in the GPe fire tonically and independently, at rates of 10-80 Hz; after dopamine depletion, GPe neurons become highly synchronized and fire in rhythmic bursts. The GPe interacts with other basal ganglia nuclei through multiple circuits, one of which, a pallidostriatal circuit linking GPe with the striatum, has only recently been identified as a natural contributor to basal ganglia rhythmicity. A major goal of this work is the identification of features within the pallidostriatal circuit that generate and maintain rhythmicity and may underlie runaway rhythmicity in pathological conditions. Achievement of this aim will help in the location of targets that can be modulated to disrupt the pathological amplification or propagation of basal ganglia rhythmicity. These results will be achieved through an approach that integrates in vivo and in vitro physiological experiments with computational model development, simulation, and analysis.","FID":206}},{"geometry":{"x":-8667389.8724,"y":4982850.017800003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Pennsylvania State Univ University Park","Title":"Theory of threshold-linear networks and combinatorial neural codes.","City":"University Park","State":"PA","Abstract":"How do connections between neurons store memories and shape the dynamics of neural activity in the brain? How do firing patterns of neurons represent our sensory experiences? The advent of technologies that facilitate simultaneous recordings of large populations of neurons present new opportunities to answer these classical questions of neuroscience. There are mathematical models that are frequently used in network simulations and data analyses that can be employed, but whose mathematical properties are still poorly understood. To guide these efforts, a better understanding of theoretical models of recurrent networks and population codes is essential. This research will focus on two such examples: threshold-linear networks and combinatorial neural codes. The goal is to produce major advances in the mathematical theory of these models, with an eye towards neuroscience applications. Part of the research will involve the analyses of neural activity in the cortex and hippocampus, in collaboration with experimentalists. Despite the focus on neuroscience, the mathematical results have the potential to be sufficiently general so as to be useful in a variety of broader contexts in the biological and social sciences.<br /><br />A threshold-linear network is a common firing rate model for a recurrent network, with a threshold nonlinearity. These networks generically exhibit multiple stable fixed points, and multistability makes them attractive as models for memory storage and retrieval. Preliminary results have shown that the equilibria possess a rich combinatorial structure, and can be analyzed using ideas from classical distance geometry. The first project will build on this understanding in order to develop a more complete picture of the structure of fixed points and higher-dimensional attractors of these networks. A combinatorial neural code is a collection of binary patterns for a population of neurons. The second project will develop an algebraic classification of combinatorial codes, using the recently developed framework of the neural ring. The neural ring encodes information about a neural code in a manner that makes properties such as receptive field organization most transparent. The resulting methods will be tested and refined using electrophysiological recordings of place cells in the hippocampus. This research will also generate new and interesting problems at the interface of neuroscience with applied algebra, combinatorics, and geometry.","FID":207}},{"geometry":{"x":-8905277.4498,"y":4929846.7337,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Carnegie-Mellon University","Title":"EAGER: Biomimetic Materials for Improving Abiotic-Biotic Signal Transduction in Brain-Machine Interfaces","City":"Pittsburgh","State":"PA","Abstract":"Non-technical<br />There are many interesting and open-ended questions regarding the function of the brain and the nervous system. The key signal transduction pathway lies between the electrical signals that are generated from excitable tissue and synthetic devices (e.g. computers and sensors) that can translate, interpret, and record this valuable information. However, the primary roadblock to seamless integration between the nervous system and computers is related to the lack of materials that can link these two disparate computing systems. The brain is soft, hydrated, and composed of neurons that use ions to communicate with one another. Conversely, silicon-based electronics are rigid, hermetically sealed, and use electrons to process information. This project will invent new biomimetic materials innovations that have the potential to bridge the tissue-device interface. These novel materials can match the mechanical properties of the brain and convert between ionic and electronic signals. Taken together, the improved electrode materials resulting from this project will create bioelectronics interfaces to learn more about the function of the brain. This project will also serve as an invaluable framework for training the next generation of materials scientists and electrical engineers. Students involved in this interdisciplinary project will receive training in polymer science, bioelectronics, and microelectronic device fabrication.<br /><br />Technical<br />This project will design and synthesize two classes of materials to improve the miniaturization of multielectrode arrays for use in brain-machine interfaces. Specifically, two materials innovations will be explored to increase charge injection limits and improve the chemical stealth of cortical brain-machine interfaces. First, nanoscale melanin films will increase the charge injection limit and promote electronic/ionic signal transduction. The rationale for this approach is based on the unique combination of nanoscale architecture, redox active chemistry, and biocompatibility that suggests that melanins can transduce ionic and electronic currents efficiently. Second, a class of ultra-compliant zwitterionic conducting hydrogel networks will be synthesized that will promote seamless mechanical, chemical, and electronic integration between electronically active implants and excitable tissue. Taken together, the materials innovations proposed herein will improve both the stimulation and recording of neural tissue using cortical brain-machine interfaces.","FID":208}},{"geometry":{"x":-8905277.4498,"y":4929846.7337,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Pittsburgh","Title":"Collaborative Research: The Ever-Changing Network: How Changes in Architecture Shape Neural Computations","City":"Pittsburgh","State":"PA","Abstract":"Our brains are constantly changing. Experiences and memories leave their imprints on connections between neurons. Understanding this process is fundamental to understanding how the brain works. While this question has been of central importance to neuroscience for decades, at this moment researchers are well positioned to make significant progress -- new recording devices and imaging techniques are revealing the activity and changes within the networks of the brain at unprecedented scale and resolution. Sound mathematical models are essential to keep up with the mounting avalanche of data. The goal of this project is to develop mathematical tools to assist with improving understanding how networks of neurons are shaped by experiences. Developing this theory is crucial for understanding learning, as well as associated disorders. The project will focus on how learning improves the brain's ability to make decisions and store memories. Graduate students and postdocs joining this project will be part of an established, interdisciplinary mathematics research community. Trainees will gain a wide perspective of mathematical neuroscience through integrated research at three institutions, including extensive visits among them. <br /><br />This research project builds on earlier results of this team to address a central challenge in the mathematical analysis of biophysically realistic neuronal networks: How brain activity changes brain structure over time. Understanding neural computation demands a description of how network dynamics co-evolves with network architecture. The research team will address this challenge by answering specific questions about the interplay between spatiotemporal patterns of neural activity, the attendant changes in network architectures, and the resulting neural computations. This project focuses on two main questions. First, what mathematical techniques can describe the co-evolution of network dynamics and network connectivity toward stable assemblies of neurons? To address this question this project will build a theory describing how global network structure evolves under the dynamics of biophysically realistic plasticity rules that operate on the scale of individual spikes and synapses. Analysis of these models requires novel multiscale and averaging methods. The resulting equations allow analysis of the stability of network architectures and their dependence on stimulus drive. With these results, the second question can be addressed: How does network plasticity create spatiotemporal dynamics that support the basic building blocks of neural computation? Models to understand how plasticity forms networks whose dynamics underlie specific operations on incoming stimuli will be developed to address this question. The mechanism by which long-term plasticity can reshape the connectivity of a network to encode a precise temporal sequence of events will also be investigated.","FID":209}},{"geometry":{"x":-8905277.4498,"y":4929846.7337,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Carnegie-Mellon University","Title":"NCS-FO: The Structure of Neural Variability During Motor Learning","City":"Pittsburgh","State":"PA","Abstract":"Movements are inherently variable: one never throws a dart or a basketball in exactly the same way twice. On the face of it, this variability in behavior is detrimental to performance, preventing one from consistently hitting the bull's-eye or making the basket. However, computational theories posit that motor variability may also serve a functional role, enabling exploration and learning of more efficient movements. This creates an intriguing duality: while variability should be minimized for short-term motor performance (to act reliably), it should be maximized for long-term performance (to promote learning). During practice, variability might be useful for developing motor skill. When it's game time, however, variability should be suppressed to the greatest extent possible. Might the central nervous system set the amount of variability in a context-appropriate fashion? This study will investigate the neural correlates of motor variability and establish the connections between neural variability, behavioral performance, and learning.<br /><br />Neural variability lies at the heart of several theoretical computational models, from implementations of probabilistic computation to Hebbian learning rules. Although the importance of variability has been well recognized, the structure and regulation of neural variability within the central nervous system is not well understood. This project coordinates a program of experiments and new analytical techniques to examine the structure of neural variability in the motor system. It seeks to establish, first, how variability depends on behavioral demands, and second, how variability impacts learning. To achieve this, many neurons of the motor and premotor cortices will be studied simultaneously during performance of demanding behaviors. By studying two distinct areas in the motor pathway, the impacts of noise on motor planning and execution can be examined separately. Furthermore, population recordings can be leveraged to decompose variability into three conceptually distinct components: (1) variability that is related to the task (signal variability), (2) trial-to-trial variability shared among neurons, and (3) private variability within each neuron. The investigators will explore how variability of each type is modulated by task context and learning. These decompositions will yield insight into the mechanisms of variability generation during performance.","FID":210}},{"geometry":{"x":-8667389.8724,"y":4982850.017800003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Pennsylvania State Univ University Park","Title":"NCS-FO: Integrative Neural Approaches to Understanding Science Text Comprehension","City":"University Park","State":"PA","Abstract":"The overall goal of this project from researchers at Pennsylvania State University is to understand the neurocognitive mechanisms underlying reading comprehension of expository scientific texts by school-aged children, adult first language readers, and adult second language readers. The proposed research integrates knowledge from several largely separate research traditions that are related to reading comprehension: (1) cognitive psychological and educational research in adult first language reading comprehension, (2) cognitive psychological and educational research in child first language reading comprehension, (3) neuroimaging research in text comprehension, and (4) graph-theoretical modeling of knowledge representation. Findings from this project will have significant implications for STEM education. It was funded by the Integrated Strategies for Understanding Neural and Cognitive Systems program, which included support from the EHR Core Research (ECR) program and the Behavioral and Cognitive Sciences division of SBE. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. <br /><br />The research team will study the behavioral and neural patterns during the reading of science text, in an attempt to unravel the brain's text reading network underlying first and second languages, and the neurocognitive differences between good versus poor readers. It combines methods from functional magnetic resonance imaging, cognitive study of learner abilities, and advanced data-analytic techniques in cognitive modeling and brain networks. The study of brain networks through the connectivity that exists in the functional and structural pathways of the learning brain holds the promise of providing new insights into the neural bases of individual differences, neuroplasticity, and language learning and representation. Data analytics will be applied to probe into the dynamic changes in connectivity patterns. This approach will allow the study not only of learning-induced or experience-dependent neural changes, but also what brain networks characterize individual differences in learning and representation (including intrinsic neural patterns captured by resting-state functional connectivity). Observed neural changes and patterns will allow the researchers to predict who might be more successful learners.","FID":211}},{"geometry":{"x":-8367045.175899999,"y":4859010.612800002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Pennsylvania","Title":"NCS-FO: The role of noise in mental exploration for learning","City":"Philadelphia","State":"PA","Abstract":"What makes people behave so differently from one another? Consider how we make decisions. Some people are quick and decisive but overly rigid, unable to adapt effectively to new opportunities or threats. In contrast, others may be more deliberative and less confident, making their decisions less predictable but more adaptable to changing circumstances. With funding from the National Science Foundation, Drs. Joshua Gold and Joseph Kable of the University of Pennsylvania are investigating a new theory that in the real world, there is a fundamental tradeoff between these two extremes. The theory includes a novel proposal that what has previously been dismissed by researchers as random variability in human behavior might instead reflect uncertain, adaptable decision-making linked with norepinephrine, a neurochemical implicated in learning and arousal. Does this characteristic explain other aspects of human personality and behavior? Can norepinephrine levels in the brain be manipulated to affect complex learning and decision-making behaviors? In answering these questions, this work will establish foundational, basic knowledge that, in the long term, will help to guide the development of new tools to diagnose and counteract conditions associated with abnormal learning and decision-making, including attention deficit hyperactivity disorder (ADHD), anxiety, depression, and schizophrenia. This knowledge about individual differences in learning will also inform how to best tailor educational and learning practices, as well as how to design computer programs that learn adaptively from experience. Other benefits of this work are resources that will assist research and education in cognitive and neural systems, including publically available datasets, computer code and machine learning algorithms; increased participation of underrepresented groups in this kind of integrative research, via summer research experiences for high school and undergraduate students; and an increased public awareness of neuroscience via public lectures, Brain Awareness Week activities, and contributions to a website that explains brain research in laymen's terms.<br /><br />The work is based on a novel hypothesis about brain mechanisms that are responsible for certain idiosyncratic learning and decision processes. Specifically, in our unpredictable world, decision-makers face an inherent trade-off: higher certainty leads to more precise and accurate choices when the world is stable but an inability to adjust to change, whereas less certainty can lead to greater adaptability but also more variable and imprecise decisions. The investigators propose that this trade-off is regulated by interactions between arousal and cortical systems. To test this hypothesis, they use an interdisciplinary and integrative set of approaches with three primary objectives: 1) develop a theoretical framework describing inherent trade-offs between output stability and learning in hierarchical, probabilistic inference processes in unpredictable environments; 2) identify behavioral, physiological, and neural correlates of variability in how individuals navigate these trade-offs while making choices in unpredictable environments; and 3) identify causal influences of the brainstem nucleus locus coeruleus, a key component of the arousal system, on the variability in adaptive inference. The work forges meaningful connections across theory and experiment, spanning multiple spatial and temporal scales and levels of abstraction, to identify computational and physiological underpinnings of individual differences in learning.","FID":212}},{"geometry":{"x":-8391016.0562,"y":4958069.156400003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Lehigh University","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Bethlehem","State":"PA","Abstract":"Space-division multiplexing optical coherence tomography for large-scale, millisecond resolution imaging of neural activity","FID":213}},{"geometry":{"x":-8532740.0004,"y":4907500.075499997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Pennsylvania State Univ Hershey Med Ctr","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Hershey","State":"PA","Abstract":"Implantable Brain Microelectromechanical Magnetic Sensing and Stimulation (MEMS-MAGSS)","FID":214}},{"geometry":{"x":-8367045.175899999,"y":4859010.612800002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Pennsylvania","Title":"Large-Scale Recording-Modulation - New Technologies","City":"Philadelphia","State":"PA","Abstract":"Biological Living Electrodes Using Tissue Engineered Axonal Tracts to Probe and Modulate the Nervous System","FID":215}},{"geometry":{"x":-9660100.3547,"y":4323740.970200002,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Vanderbilt University","Title":"Next Generation Human Imaging","City":"Nashville","State":"TN","Abstract":"Neuron selective modulation of brain circuitry in non-human primates","FID":216}},{"geometry":{"x":-9342032.8655,"y":4295186.711199999,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Tennessee Knoxville","Title":"Multi-functional Polymer Structures for Promoting Neurite Extension and Myelination","City":"Knoxville","State":"TN","Abstract":"Non-Technical: <br />Each year in the U.S., several million people suffer from peripheral nerve injuries that occur with accidental trauma or during the course of surgery. Failure to restore damaged nerves leads to the loss of muscle function, impaired sensation, and painful neuropathies. Autologous nerve graft, the \"gold standard\" in surgery, has disadvantages such as limited source, additional surgery, and mismatch between injured nerve and donor nerve. Synthetic nerve conduits are thus needed for bridging the long gap between injured peripheral nerve stumps. Polymers used for fabricating suitable nerve conduits should have capability of resisting tear, suturability, and ease of incorporation with support cells and nerve growth factor (NGF). There only exist a few crosslinkable and biodegradable ones for microfabrication of nerve conduits and it is largely unknown how to achieve optimal material environment to maximize neuronal and glial cell functions and axonal growth. The PI proposes an innovative and unique solution to manufacture biodegradable polymer nerve conduits with complex multi-component structures and multiple functionalities. By performing comprehensive, systematic studies using a wide range of physicochemical and structural characteristics of polymers, the PI will achieve both fundamental understanding and practically useful medical devices for fostering the synergistic transfer of know-how among research communities of materials, biomedical engineering, and medicine.<br /><br />Technical: <br />The PI proposes to integrate photo-reactive, biodegradable polymers synthesized from poly(ethylene glycol), poly(epsilon-caprolactone), and poly(L-lysine), and bioactive reagents (e.g., NGF and cell-adhesive peptides), via solvent-free processes into multi-component, multi-functional structures with a wide range of physicochemical properties and structural features for promoting peripheral nerve repair. Using these polymer structures, the PI proposes to achieve fundamental understanding how polymer physicochemical properties regulate the behaviors and functions of both neuronal (e.g., dorsal root ganglion neurons) and glial cells (e.g., conditionally immortalized Schwann cell precursor line cells), and then optimized to maximize neurite extension and myelination. As well as the materials and processing parameters, the optimized polymer structures will guide more precise micro-fabrication of nerve conduits, and their in vivo animal implantation and histological analysis. The proposed fabrication method and drug delivery systems can also be applied to other tissue engineering applications. The PI proposes to provide an open access of scaffolding and cell regulation; curriculum on Biomaterials Fabrication and Processing; summer research experience for undergraduates, minorities, and underrepresented groups; disseminate discoveries to K-12 students through outreach programs; and develop lab/course modules for public high-school teachers and students through Pre-collegiate Research Scholars Program and distance education.","FID":217}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Texas Hlth Sci Ctr Houston","Title":"Tools for Cells and Circuits","City":"Houston","State":"TX","Abstract":"Anion channelrhodopsin-based viral tools to manipulate brain networks in behaving animals","FID":218}},{"geometry":{"x":-1.08806994949E7,"y":3537993.0471,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Texas, Austin","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Austin","State":"TX","Abstract":"A robust ionotropic activator for brain-wide manipulation of neuronal function","FID":219}},{"geometry":{"x":-1.08806994949E7,"y":3537993.0471,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Texas, Austin","Title":"Large-Scale Recording-Modulation - New Concepts/Early Stage Research","City":"Austin","State":"TX","Abstract":"A viral system for light-dependent trapping of activated neurons","FID":220}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"Baylor College Of Medicine","Title":"Understanding Neural Circuits","City":"Houston","State":"TX","Abstract":"Dynamic network computations for foraging in an uncertain environment","FID":221}},{"geometry":{"x":-1.08806994949E7,"y":3537993.0471,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NIH","Institution":"University Of Texas, Austin","Title":"Understanding Neural Circuits","City":"Austin","State":"TX","Abstract":"Neural ensembles underlying natural tracking behavior","FID":222}},{"geometry":{"x":-1.07752144577E7,"y":3865894.5156999975,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Nerves Inc.","Title":"HAPTIX","City":"Dallas","State":"TX","Abstract":"Develop neural interfaces to improve fine motor control and restore sense of touch and proprioception for prosthetics users.","FID":223}},{"geometry":{"x":-1.07752144577E7,"y":3865894.5156999975,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"University Of Texas At Dallas","Title":"ElectRx","City":"Dallas","State":"TX","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":224}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"William Marsh Rice University","Title":"NSF Ideas Lab - Cracking the Olfactory Code","City":"Houston","State":"TX","Abstract":"Olfaction is an evolutionarily primitive sense critical for survival across the animal kingdom - finding food, searching for mates, or avoiding predation all depend on detecting, identifying, and discriminating odors. Although early steps in olfactory processing are relatively well understood, significant gaps remain in our understanding of higher-order odor representations and processing during on-going behavior. Deciphering the operating principles of olfaction requires the development of innovative and integrative approaches that combine novel theoretical frameworks, improved mathematical models, and novel behavioral paradigms across the phylogenetic spectrum, experimental methodologies, and engineering principles. The objectives of this 5-day workshop, a so-called \"Ideas Lab\", is to address this challenge by bringing together researchers from diverse scientific backgrounds to engender fresh thinking and innovative approaches that will transform understanding of olfactory processing in behavioral contexts while spawning new opportunities to elucidate the general nature of sensory representations in the brain. The participants will work collaboratively to develop and hone novel ideas about and approaches to investigate olfactory processing, and then use these ideas and approaches to develop multidisciplinary research projects that contain genuinely innovative and potentially transformative investigations on olfactory coding. <br /><br />The organizers will make a strong effort to invite women, members of underrepresented groups, and investigators at all academic levels as workshop participants. Participants will include 10-15 quantitative researchers and 15-20 neuroscientists. An integral aspect of the workshop is extensive cross-disciplinary interaction, which will be facilitated by five leading scientists from key disciplines who have agreed to serve as mentors and will guide the project development process. Importantly, this workshop is part of a concerted effort to coordinate and align interagency priorities to accomplish the goals of the BRAIN Initiative. The workshop is anticipated to result in the development of highly innovative research proposals that integrate theoretical and computational approaches with neuroscience toward the goal of elucidating the nature of olfactory processing and sensory representations in the brain in general.","FID":225}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"William Marsh Rice University","Title":"BRAIN: EAGER: Memory Reactivation in Neural Circuits Over Long, Continuous Timescales","City":"Houston","State":"TX","Abstract":"Memories of facts and experiences take time to be stored robustly in the brain. Understanding of the underlying mechanisms would not only yield insight into a fundamental ability found in all animals, but also allow for the optimization of learning and memory in healthy individuals as well as interventions in humans with compromised memory. Many current hypotheses of memory posit the importance of \"replay\" within ensembles of neurons in the brain. The idea is that in periods of quiescence or sleep, neurons in the hippocampus, a key brain structure for memory, re-excite the patterns of activity that occurred during the original learning/experience. This neural replay of the original activity patterns enables distributed cortical regions to form robust, lasting interconnections and thereby support memory. In rats learning to navigate mazes, the signals of dozens of individual hippocampal neurons can be accessed simultaneously. In this project, neural recording, computational, and statistical tools are developed and tested to observe neuronal activity in the hippocampus of rats over long periods of time-- periods that include repeated active learning and quiescence/sleep episodes-- and address fundamental questions about replay and how individual neurons participate in replay/learning over time. The algorithms developed in this project are shared widely through on-line media. The data collected contribute to instructional material used in interdisciplinary graduate training programs and courses focused on neural signal processing.<br /><br />In this project, new neural recording technology and novel and computational analysis techniques are used to acquire and interpret week-long continuous recordings of hippocampal activity while an animal learns a novel task. The result is the first ever qualitative and quantitative assessment of replay over a period of this length. The resulting data have the potential to yield great insight into how changes in patterns of neural activity at the scales of milliseconds (replay) interact with changes at the scales of hours (circadian) and days (learning). The algorithms developed, which are shared through a public on-line site, may be foundational to a new experimental paradigm where neurons are recorded continuously over time. A particularly valuable outcome of the project are novel algorithms for automatically isolating the signals of individual neurons from each other, and tracking slow changes to their signatures over time. Additionally, a new latent-variable model technique for quantifying how individual replay events compare with the patterns exhibited during learning enables the statistics of replay variability to be assessed. The impacts of this work have the potential to be broad, from techniques that revolutionize systems neuroscience to data that underpins new models of learning and memory.","FID":226}},{"geometry":{"x":-1.09643694276E7,"y":3429797.6389999986,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Texas Health Science Center San Antonio","Title":"Understanding How BK Potassium Channels Enhance a Neuron's Input/Output Function","City":"San Antonio","State":"TX","Abstract":"Brain function is dependent upon proteins that allow ions to pass across neuron cell membranes (called ion channels) to create currents that mediate the electrical activity of neurons. Protein channels that permit potassium ions to pass through neuron membranes are generally thought to quiet excessive neuron activity. However, there is a growing list of examples indicating that these \"BK-type\" potassium ion channels may also increase neuron excitability. The fact that BK channels are expressed throughout the nervous system suggests that understanding such paradoxical effects is important for understanding brain function in general. The investigators will record the activity of neurons in mice to learn the conditions that cause BK channels to quiet or excite neurons. The results will be used to make computational models that predict the anti-excitatory or pro-excitatory behaviors of BK channels. The project will train graduate students and a postdoctoral fellow to use state-of-art methods for studying brain function and anatomy and to make computational models, and will support the development of an integrated online virtual laboratory, \"The Ion Channel laboratory,\" to teach users about ion channels and the electrical excitability of neurons. <br /><br />The mechanisms underlying how slow- and fast-gating BK channel types either depress or paradoxically enhance a neuron's likelihood for firing an action potential (AP) will be studied in dentate gyrus neurons of the hippocampus. Using wild type neurons that express slow-gating BK channels, and transgenic neurons (BK beta4 knockout) that express fast-gating channels, the investigators will directly measure the cause-and-effect relationship between BK-regulated AP shape, activation of spike-triggered bulk and local calcium, recruitment of interspike conductances, and AP frequency. These data will be used to generate a computational model of dentate gyrus neurons that predicts the context in which BK channels reduce or enhance neuronal excitability. The model will then be experimentally tested in hippocampus CA1 pyramidal cells and cerebellum purkinje neurons to determine if pro-excitatory effects uncovered in dentate gyrus neurons are features observed in other neuron types that express BK channels. The findings of this study will create new understanding and new neuronal computational models of spike-influenced conductance and its effect on intrinsic excitability.","FID":227}},{"geometry":{"x":-1.09643694276E7,"y":3429797.6389999986,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Texas At San Antonio","Title":"Interagency BRAIN Intitiave Awardees Meeting in Bethesda, MD, November 20-21, 2014","City":"San Antonio","State":"TX","Abstract":"Understanding how behavior emerges from the dynamic patterns of electrical and chemical activity of brain circuits is universally recognized as a fundamental mystery in science. Modern neuroscience has made great strides towards this goal by utilizing advances in multiple scientific disciplines. These developments have brought the field to a unique moment, where a revolution in understanding the brain appears to be within our grasp. Capitalizing on this unique moment, the BRAIN Initiative was created to catalyze national efforts toward understanding the brain. As part of the BRAIN Initiative, NSF will enable the development of an array of physical and conceptual tools needed to determine how healthy brains function. In Fiscal Year 2014, NSF made 36 Early Concept Grants for Exploratory Research (EAGER) awards aimed at catching neural circuits in action. This award will support a workshop to convene awardees from the NSF BRAIN EAGER competition and awardees from other federal BRAIN Initiative efforts. The objectives of this workshop are to identify conceptual foundations and challenges in data management and technology implementation. The participants will discuss these issues in small thematic groups, and will use their insights to generate a coherent set of strategies and expectations towards the goals of the BRAIN Initiative. <br /><br />The Organizers are making a strong effort to invite women and members of underrepresented groups as participants. Further, the meeting entails extensive cross-disciplinary interactions, which will be aided greatly by the face-to-face nature of this meeting. Importantly, this workshop is part of a concerted effort to coordinate and align interagency priorities to accomplish the goals of the BRAIN Initiative. To maximize the workshop's impact, video recordings of introductory sessions will be disseminated through a publicly accessible web-site.","FID":228}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"William Marsh Rice University","Title":"NCS-FO: Identifying Design Principles of Neural Cells","City":"Houston","State":"TX","Abstract":"PI: Qutub, Amina <br />Proposal Number: 1533708<br /><br />This proposal seeks to develop a robust theory of how single neural cells form electrically active networks. The project integrates emerging methods in computer science, systems biology, neuroengineering and developmental biology to offer insight into the brain's organization. Results of experiments performed in this project have the potential to impact the design of new computing devices, a $300B industry. Methods introduced by the investigators can be used broadly by scientists to rapidly characterize brain cells, and can aid in the discovery of new therapies for neurological diseases, which affect 1 in 6 people worldwide.<br /><br />Neural differentiation, the process of neural progenitor cells transforming into neurons, holds the key to understanding the brain's ability to self-repair. Understanding this complex process can inform us how the structure of neural networks relates to their function, which is an important unsolved problem in neuroengineering. This project's ultimate goal is a mechanistically-detailed theory of how neural networks form as a result of decisions made by single neural progenitor cells. Integrating methods from three disciplines (systems biology, nanotechnology and developmental biology), the investigators will identify single cell features critical to network formation, and predict how heterogeneity and noise in the cell population defines the network's function. The investigators will employ three emerging methods (proteomic barcoding, ImageOmics, and E-phFACS) to define neural cell phenotypes as a function of chemical signaling, morphology and electrical activity (Aim 1). Observed changes in these single cell phenotypes will be mapped to neural network formation by coupling a state machine model with a graph-based analysis (Aim 2). The effects of cell heterogeneity will be explored computationally using a new framework developed by the investigators and iteratively compared to in vitro live-imaging assays, and in vivo assays. The tight coupling of chemical, morphological and electrical measurements enabled by the technologies introduced here, can be broadly applicable paradigm for integrative scientific research. Understanding how cells interact to form neural networks has relevance to organism development and tissue engineering. State-machines can be adapted across tissues and species to develop theories of cell decision-making. The phenotyping tools that correlate electrophysiology and protein expression with multi-cellular network topology will provide a powerful resource for neurobiologists. Furthermore, the E-phFACS device provides a high-throughput way to record electrical activity and sort cells. To further engage the scientific community, the investigators will (1) provide an open source ImageOmics platform and (2) host an international crowd-sourced neuronal network Design Challenge.","FID":229}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Houston","Title":"Planning Grant: Collaborative Research: I/UCRC for Building Reliable Advances and Innovation in Neurotechnology (BRAIN)","City":"Houston","State":"TX","Abstract":"This project will bring together teams from Arizona State University and University of Houston in collaboration with industry partners to establish a research center, called BRAIN (Building Reliable Advances and Innovation in Neurotechnology) that will overcome several innovation challenges in neurotechnology: 1) The pace of innovation exceeds the rate of evaluation for acceptable performance; 2) Standards and regulatory science for rigorous validation of safety, efficacy, and long-term reliability are missing; 3) Lack of open access to technologies and synergistic collaborations impede transfer of novel technologies to the market; and 4) Current technologies are costly, limiting their utility in enhancing treatment and overcoming physical disabilities. In addition, the BRAIN Center, through the efforts of the Education/Outreach coordinator, will work to rectify under-representation in the science, technology, engineering, and math (STEM) fields by broadening new participation and retaining current participants in STEM through 1) newly initiated K-12 outreach programs that expose aspiring STEM participants to innovative neurotechnologies, 2) undergraduate internship program within the Center that targets specific student organizations (e.g., Society of Mexican-American Engineers and Scientists, Society of Women Engineers), and 3) focusing on problems in the neurological space that affect underrepresented groups disproportionately. <br /><br />The Center's vision is a synergistic, interdisciplinary approach to the development and validation of affordable patient-centered technologies, and use of those technologies in understanding neural systems. BRAIN will leverage expertise in neural, cognitive and rehabilitation engineering, robotics, clinical testing, and reverse-translational research at Arizona State University (ASU) and the University of Houston (UH) to (a) enhance the rate of development and empirical validation of new technologies through partnerships with industry leaders and other strategic partners; (b) develop standards and test technologies in human and non-human models using a multi-scale approach ranging from single neurons to organismal systems; (c) characterize novel and innovative technologies such as biosensors and quantitative analysis tools for systems and behaviors; (d) evaluate the impact of these technologies on quality of life; and (e) reduce the cost burden of neural technologies on hospitals and families.","FID":230}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"William Marsh Rice University","Title":"Collaborative Research: PoLS Student Research Network","City":"Houston","State":"TX","Abstract":"This collaborative research project, consisting of four institutions (Rice, Yale, UIUC and Princeton) aims to continue the Physics of Living Systems Student Research Network (PoLS SRN). This network has been in existence for four years and has had a dramatic impact on many graduate students, both in the US and abroad, working on the application of physical science techniques to living systems. These students now can participate in a global community that can help deal with the many complex issues involved in conducting research in such a new and inherently multidisciplinary field. These issues range from proper training, to gaining a broad perspective, to accessing technical expertise that may not be available at their home institution. In addition to the obvious broader impacts related to training of a research workforce, there are other broad impacts of this plan. Via the interaction of one of the PoLS nodes (Rice) with the biomedical community in Houston, students and faculty will be exposed to possible avenues whereby physics can contribute to human health issues. Funds to attract students from under-represented groups to network meetings will be available through the new funds administered by the newly proposed network coordinator. Also deas vetted by the PoLS SRN will be adapted to create student networks in other areas of science and engineering.<br /><br />There is by now little disagreement with the general notion that concepts and methods from physics have been a critical contributor to the increased understanding of the living world, and that its importance will be growing as the scientific world moves toward an ever more quantitative and predictive form of biology. Thus, the physics community clearly needs to train a new generation of scientists who can lead this effort, scientists who have the right mix of physics/mathematics rigor and broad knowledge of living systems from molecular scales on up. The PoLS SRN aims at creating a community of graduate students who can collectively help themselves and their mentors accelerate and enhance this training process. This is being done by a mix of in-person and virtual modes of communication, and this proposal is a plan to continue and expand these efforts; it will reach more students, improve the social networking portals, and make use of the complementary research agendas of the different network nodes to provide broad technical expertise. Doing all of this, will boost the intellectual level of the entire research field and convince the best students that the Physics of Living Systems is truly the most exciting research frontier in 21st century science.<br /><br />This project is being jointly supported by the Physics of Living Systems program in the Division of Physics, the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences, the Chemistry of Life Processes program in the Division of Chemistry, and the Cellular Dynamics and Function Program in the Division of Integrative Organismal Systems.","FID":231}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Houston","Title":"Non-Equilibrium Statistical Mechanics of Co-Evolving Complex Systems","City":"Houston","State":"TX","Abstract":"NONTECHNICAL SUMMARY<br /><br />This award supports research and education aimed to find fundamental principles that govern the behavior of complex systems, an important and challenging problem. A complex system often consists of components that each behave in a well-defined way, but when combined display new distinctly different behavior that is more than the sum of the individual behaviors. The new behavior is said to be emergent. The components of complex systems often have heterogeneous properties and interactions. Examples abound in nature, ranging from the brain and the regulatory systems of cells in biology, to social networks and ecosystems, and from interdependent infrastructure networks in engineering to atmospheric and oceanic dynamics. A principal difficulty in understanding many complex systems is that their dynamics is driven by external mechanisms that prevent them from reaching the steady state of equilibrium. Thus, the foundational principles that govern equilibrium systems, discovered over a century ago, typically do not apply to them. The analogous principles of driven, non-equilibrium systems are poorly understood, necessitating the need for finding the foundational principles of the behavior of non-equilibrium systems and for understanding the range of their possible behavior. This award supports research to address this problem by focusing on three different types of non-equilibrium complex systems and their generalizations. Each system is motivated as a model that captures the essence of real neural, biological or social behavior, and so, understanding their specific properties is important. The goal is either to develop or enhance mathematical methods and tools that can be used generally to study co-evolving complex systems, and thus, to gain transformational insight into complicated systems such as the human brain.The work on each of the systems will build on recent preliminary results obtained by the investigators in their ongoing research effort. The research will be both analytical and computational, and will range from fundamental problems in mathematical physics, to the analysis and application of the fundamental ideas to real - world experimental data. <br /><br />The funded activities will significantly contribute to ongoing efforts at the University of Houston in both Computational and Network Science. These efforts foster interdisciplinary collaboration within the University and with local industry. The PI and his group will participate in outreach activities for the community each year. The PI will also continue to teach multidisciplinary graduate courses he has designed to broadly educate students about recent advances in both Computation and Network Science. The grant will also support the PI's service as a faculty facilitator in the continuing education training each year for 20 teachers without a physics background that teach physics to approximately 3000 students in high-need school districts in the Houston area. It will also support the Co-PI's collaboration on a new text that teaches physics to students in the biological sciences. His focus is on explaining the central role that understanding systems far from equilibrium plays in all biological organisms. The graduate students supported by the grant will be trained in broadly applicable analytic and computational skills that will prepare them for a wide range of career opportunities. They will also contribute to the planned educational and outreach activities. Involving people from under-represented groups in this work will also be a focus. <br /><br /><br />TECHNICAL SUMMARY<br /><br />This award supports research and education aimed to find fundamental principles that govern the behavior of complex systems. A principal difficulty in understanding many complex systems is that their dynamics is driven by exogenous mechanisms, preventing them from reaching thermal equilibrium. Unlike equilibrium statistical mechanics, the principles of nonequilibrium statistical mechanics remain poorly understood. Yet, such systems are ubiquitous, ranging from the neural, genetic, and metabolic regulatory systems in biology, to population dynamics and competition in social systems and ecosystems, and from interdependent infrastructure networks to atmospheric/oceanic dynamics at the global scale. Establishing the foundational principles of nonequilibrium statistical mechanics as they apply to complex systems would transform not only our understanding of nature, but also our ability to control it. In order to establish the principles of nonequilibrium statistical mechanics, it is helpful to understand the range of possible behavior in complex systems, driven far from equilibrium. A particularly challenging set of such systems to understand is those in which two or more distinct components co-evolve in an interdependent manner. Systems structured as complex networks that have interdependent dynamics in both node- and link- degrees of freedom are prime examples of co-evolving complex systems. <br /><br />The research will involve three sets of simple model network systems that capture the essence of non-equilibrium behavior found in nature. These models are also chosen because they can be efficiently simulated numerically, and have some aspects that can be understood analytically. The PIs will combine careful simulations with analytic calculations, to gain insight into both fundamental issues in non-equilibrium statistical mechanics, and to develop deeper understanding of the intriguing phenomena displayed in real-world systems. The first set of projects will study the co-evolutionary dynamics of social network models consisting of interacting agents endowed with a temperament as either introverts or extroverts. Game-theoretic node dynamics will be combined interdependently with link dynamics due to the temperament of the nodes. These models merge two paradigms of non-equilibrium statistical mechanics, one for the node dynamics and the other for the link dynamics, to explore new co-evolutionary phenomena. The second set of projects will study the adaptive dynamics of Boolean networks in which both nodes and links co-evolve. They are prototypical examples of heterogeneous complex systems and as such present distinct challenges to their understanding. They were originally proposed as simple models of genetic regulatory systems, and recently have become widely used as simple models of neural systems. Understanding the co-evolution of the network structure and the rules of node behavior of these models may unlock keys to understanding neural function. Finally, the third set of projects will extend the PI's recent work on the co-evolutionary dynamics leading to Emergent Speciation, a novel method of biological speciation that may be a root cause of the origin of the species.","FID":232}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"William Marsh Rice University","Title":"Topological Insulators by Band-Gap Engineering","City":"Houston","State":"TX","Abstract":"Nontechnical description:<br />Electrical insulators are commonly recognized as materials that prevent the flow of electricity. However, recent research demonstrates a type of topological insulators which has novel properties. Although electricity cannot flow through them, it can flow around their narrow outer edges. The material, called a \"quantum spin Hall topological insulator\", acts as an electron superhighway. It is one of the building blocks needed to create future electronics and computers. In this project the principle investigator will perform experiments on the newly discovered topological insulators made of compound semiconductors indium arsenide and gallium antimonide, addressing important issues relate to materials science and quantum physics. Understanding of materials science of this class of material and their topological properties is directly relevant to spintronics and quantum information technology.<br /><br />Technical descripton:<br />The two-dimensional topological insulator, which supports quantized helical edge modes, is created by band-gap engineering using molecular beam epitaxy and electrostatic gates. The project is exploring interesting physics at the messoscopic length scale, with the focus on the helical edge modes and their interface with superconductors, where proximity effect and Andreev reflection are being systematically studied. Major focus of the study is searching for Majorana bound states in hybrid topological insulator-superconductor Josephson junctions. The experimental research work addresses fundamental phenomenon and its physics in a very clean model system. The project supports the education of two Ph.D. students, where they receive a combination of advanced training in semiconductor materials, nanotechnology, and ultra-low temperature measurements.","FID":233}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Houston","Title":"Collaborative Research: The Ever-Changing Network: How Changes in Architecture Shape Neural Computations","City":"Houston","State":"TX","Abstract":"Our brains are constantly changing. Experiences and memories leave their imprints on connections between neurons. Understanding this process is fundamental to understanding how the brain works. While this question has been of central importance to neuroscience for decades, at this moment researchers are well positioned to make significant progress -- new recording devices and imaging techniques are revealing the activity and changes within the networks of the brain at unprecedented scale and resolution. Sound mathematical models are essential to keep up with the mounting avalanche of data. The goal of this project is to develop mathematical tools to assist with improving understanding how networks of neurons are shaped by experiences. Developing this theory is crucial for understanding learning, as well as associated disorders. The project will focus on how learning improves the brain's ability to make decisions and store memories. Graduate students and postdocs joining this project will be part of an established, interdisciplinary mathematics research community. Trainees will gain a wide perspective of mathematical neuroscience through integrated research at three institutions, including extensive visits among them. <br /><br />This research project builds on earlier results of this team to address a central challenge in the mathematical analysis of biophysically realistic neuronal networks: How brain activity changes brain structure over time. Understanding neural computation demands a description of how network dynamics co-evolves with network architecture. The research team will address this challenge by answering specific questions about the interplay between spatiotemporal patterns of neural activity, the attendant changes in network architectures, and the resulting neural computations. This project focuses on two main questions. First, what mathematical techniques can describe the co-evolution of network dynamics and network connectivity toward stable assemblies of neurons? To address this question this project will build a theory describing how global network structure evolves under the dynamics of biophysically realistic plasticity rules that operate on the scale of individual spikes and synapses. Analysis of these models requires novel multiscale and averaging methods. The resulting equations allow analysis of the stability of network architectures and their dependence on stimulus drive. With these results, the second question can be addressed: How does network plasticity create spatiotemporal dynamics that support the basic building blocks of neural computation? Models to understand how plasticity forms networks whose dynamics underlie specific operations on incoming stimuli will be developed to address this question. The mechanism by which long-term plasticity can reshape the connectivity of a network to encode a precise temporal sequence of events will also be investigated.","FID":234}},{"geometry":{"x":-1.07229497631E7,"y":3583566.593999997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Texas A&M University Main Campus","Title":"Studies on Signals and Images via the Fourier Transform","City":"College Station","State":"TX","Abstract":"The goal of this project is to develop novel statistical methods that address some of the current challenges in analyzing spatio-temporal data frequently encountered in neuroimaging. One major application of this project is to identify features in brain signals that could differentiate healthy individuals from patients with neurological or mental diseases. The second application is to identify changes that take place in a brain signal during cognitive processing (e.g., while a human learns a new motor skill or while a rat learns risks and rewards in a controlled experiment). The third application is to identify biomarkers in brain signals that could predict a stroke patient's ability to recover loss of motor functionality. The approach used to solve these problems requires a study of the oscillatory patterns in these brain signals. <br /><br />Motivated by these practical problems, statistical methods based on the discrete Fourier transform (DFT) are developed. The DFT gives an indication of the decomposition of variance in the time series. Under stationarity, the covariance of the DFT is sparse and thus a departure from sparsity is an indication of non-stationarity. Moreover, the covariance of the DFT can be utilized as a discriminator between classes of signals. Using the properties of the DFT, novel methods for (1) change-point detection in time series based on sparsity of the DFT, and (2) discrimination and classification of classes of time series based on the properties of the covariance of the DFT will be developed. The DFT will also be used to estimate the variance of functionals of the spectrum and test for serial correlation and stationarity in nonlinear time series. Validation for stationary spatial processes and non-stationary spatial processes using the two-dimensional DFT will also be developed.","FID":235}},{"geometry":{"x":-1.18541327097E7,"y":3731738.352300003,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Texas At El Paso","Title":"Bayesian Time Series Methods in the Frequency Domain","City":"El Paso","State":"TX","Abstract":"This project focuses on developing novel statistical methods for the analysis of dependent data arising in biomedical applications. Often, frequency patterns in such data contain interpretable scientific information. The main motivating applications in this project include epilepsy-related EEG (electroencephalogram), sleep, and DNA sequence data. In epilepsy research, advance warning of an epileptic seizure based on the analysis of intracranial EEG could minimize injury, and give patients a sense of control in their management of the disease. Simultaneous analysis of multiple channels may lead to more accurate estimates, compared to separate analyses of signals from individual channels. The proposed methodology will also be used to analyze data from the AgeWise study to help understand the connections between self-reported measures of sleep and electrophysiological signals.<br /><br />This project is focused on adaptive spectral estimation for nonstationary multivariate time series using Bayesian modeling that relies on Markov chain Monte Carlo methods for the estimation. Methods are developed for estimating local spectra of qualitative or quantitative bivariate and trivariate nonstationary time series. The multivariate Whittle approximation is used for approximating local likelihoods corresponding to small segments of the time series. Each approximate local likelihood is a function of the discrete Fourier transform of the segment and the corresponding local spectral matrix. Spectral matrices are expressed as modified Cholesky decompositions, thus allowing estimation that guarantees Hermitian and positive definite matrices. Smoothing splines are used for estimating the elements of the spectral matrices as a function of frequency. Additionally, the proposal develops methodology for the analysis of time series collected along with covariates on multiple subjects, where the goal is to model spectral matrices as a function of both frequency and covariates. The proposed methods are applied to the analysis of intracranial EEG signals from two channels in the brain of an epileptic patient, sleep data on older adults from the AgeWise study, and DNA sequences.","FID":236}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"William Marsh Rice University","Title":"NCS-FO: Collaborative Research: Micro-scale Real-time Decoding and Closed-loop Modulation of Human Language","City":"Houston","State":"TX","Abstract":"Humans produce language, which is a defining characteristic of our species and our civilization. We can select words precisely out of a large lexicon with remarkably low error rates. It is perhaps not surprising that this complex speech production system is easily affected by disease. Brain damage induced language disorders affect millions of Americans, and there is little hope of remediation. Research on the anatomical, physiological, and computational bases of speech production has made important strides in recent years but this has been limited by a glaring lack of information on the dynamics of the process. This limitation results from the low spatio-temporal resolution of the available tools to collect data and the effectiveness of the current tools for analysis. Our driving vision in this project is to develop an unparalleled understanding of cortical connectivity in the human language system at small spatio-temporal scales. We possess much expertise in signal decoding of the processes of cued word production with intracranial recording techniques, as well as using cortical stimulation to modulate the system. FDA-approved arrays will be used to perform closed-loop decoding of sensorimotor processes during speech production and transient neuromodulation of the language system in patients with epilepsy undergoing intracranial electrode placement for the localization of seizures. Ultimately though, the fine-grained understanding and representation of sensorimotor loops in the language system necessitates the development of ultra-small energy efficient detectors that will enable the knowledge gained in this exploratory project to be eventually applied in patients who have sustained neurological injuries that have resulted in pervasive language impairments. This integrative project brings innovative microelectronics technologies together with state of the art large data analysis techniques to begin to develop a first of its kind system to remediate language disorders.<br /><br />The engineering objective is to develop biocompatible microchips to vastly enhance our insight into language and other cognitive processes and learning. Miniaturized microchips in silicon technology will be developed that can record neural signals, digitize them, and transmit the signals to an in vitro receiver wirelessly. The three-fold thrust of the project will be integrated when the PIs develop closed-loop real time decoding and transient neuromodulation system based on a population of miniaturized detectors and neuromodulators. The system has the potential to provide an unprecedented detailed understanding of the human language system and provide the framework and hardware for neural prosthetics in patients with aphasia and other language disorders. The project embodies multiple high-risk goals that have the potential to shift neuroengineering paradigm from recording and modulating in only a few regions of the brain to deploying a population of ultra-small and energy efficient detectors-modulators.","FID":237}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Houston","Title":"NCS-FO: Assaying neural individuality and variation in freely behaving people based on qEEG","City":"Houston","State":"TX","Abstract":"This project will deploy noninvasive Mobile Brain-body Imaging devices (MoBI) in a public museum with the goal of assaying individuality and variation in neural activity as it occurs (e.g., \"in action and context\") in a large and diverse group of people, including children, experiencing fixed and interactive art exhibits. A natural setting such as an art museum attracts thousands of people with rich demographic factors such as age, sex, education level, occupation, and other factors such as health, medication and neurological status, thereby providing a unique opportunity to study the population distribution, accuracy and stability of neural activity and advance understanding of the dynamics of complex neural and cognitive systems in natural environments. The broader impacts of this research include integrating the arts, science and engineering to advance brain science; advancing the regulatory science of biomedical devices by uncovering biometric neural data as objective endpoints to investigate cognition, perception and action; supporting and promoting STEM education, and advancing the field through dissemination and data sharing of products generated in this research. Importantly, the efficacy and related safety of MoBI-based diagnostics and therapeutics depend on scientific understanding of neural variability and individuality. In the same way that individual variation in gene sequences makes certain drugs more or less effective for certain people, giving rise to the need for pharmacogenomics, individual variation in brain activity will not only affect the assessment of drugs which use these endpoints, but will also strongly affect the safety and efficacy of therapeutic medical devices. Despite this critical importance, there is no concerted effort elsewhere to address these basic questions that are holding back the research and development of novel noninvasive biomedical devices with all of its diagnostic benefits that could also contribute to reverse engineer brain mechanisms. <br /><br />A big-data analytics approach for investigating neural variability and individuality in brain data from a large number of diverse participants could help advance development of biomedical devices while filling knowledge gaps in brain science. Three research objectives will be pursued to produce this science while developing novel tools for discovery. First, this project entails the acquisition of multi-modal data from a thousand participants from the diverse Greater Houston area. Second, the research will develop novel algorithms for analyzing, inspecting, visualizing, representing, parsing, and searching high-dimensional patterns from the multi-modal datasets acquired in a public setting at the Blaffer museum. The goals are to uncover neural signals associated with the passive and interactive perception/production of art and to assess the long-term stability of neural activity acquired via quantitative electroencephalography (or qEEG). The proposed project will lead to innovative time-resolved methods and tools to study the population distribution, accuracy and stability of neural activity. Third, the project will generate a unique big dataset, and algorithms that will be shared with the scientific community. This research opens new scientific and educational horizons for addressing empirical problems (e.g., the acquisition of multimodal data from freely behaving subjects in public settings), and normative problems (e.g., decoding human intent and emotion from patterns of brain activity) in science. Moreover, the project will enable K-12 to postdoctoral training of a diverse population of students/trainees.","FID":238}},{"geometry":{"x":-1.06165150167E7,"y":3472795.434299998,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Texas Health Science Center Houston","Title":"NCS-FO: Collaborative Research: Micro-scale Real-time Decoding and Closed-loop Modulation of Human Language","City":"Houston","State":"TX","Abstract":"Humans produce language, which is a defining characteristic of our species and our civilization. We can select words precisely out of a large lexicon with remarkably low error rates. It is perhaps not surprising that this complex speech production system is easily affected by disease. Brain damage induced language disorders affect millions of Americans, and there is little hope of remediation. Research on the anatomical, physiological, and computational bases of speech production has made important strides in recent years but this has been limited by a glaring lack of information on the dynamics of the process. This limitation results from the low spatio-temporal resolution of the available tools to collect data and the effectiveness of the current tools for analysis. Our driving vision in this project is to develop an unparalleled understanding of cortical connectivity in the human language system at small spatio-temporal scales. We possess much expertise in signal decoding of the processes of cued word production with intracranial recording techniques, as well as using cortical stimulation to modulate the system. FDA-approved arrays will be used to perform closed-loop decoding of sensorimotor processes during speech production and transient neuromodulation of the language system in patients with epilepsy undergoing intracranial electrode placement for the localization of seizures. Ultimately though, the fine-grained understanding and representation of sensorimotor loops in the language system necessitates the development of ultra-small energy efficient detectors that will enable the knowledge gained in this exploratory project to be eventually applied in patients who have sustained neurological injuries that have resulted in pervasive language impairments. This integrative project brings innovative microelectronics technologies together with state of the art large data analysis techniques to begin to develop a first of its kind system to remediate language disorders.<br /><br />The engineering objective is to develop biocompatible microchips to vastly enhance our insight into language and other cognitive processes and learning. Miniaturized microchips in silicon technology will be developed that can record neural signals, digitize them, and transmit the signals to an in vitro receiver wirelessly. The three-fold thrust of the project will be integrated when the PIs develop closed-loop real time decoding and transient neuromodulation system based on a population of miniaturized detectors and neuromodulators. The system has the potential to provide an unprecedented detailed understanding of the human language system and provide the framework and hardware for neural prosthetics in patients with aphasia and other language disorders. The project embodies multiple high-risk goals that have the potential to shift neuroengineering paradigm from recording and modulating in ?only? a few regions of the brain to deploying a population of ultra-small and energy efficient detectors-modulators.","FID":239}},{"geometry":{"x":-1.24553392711E7,"y":4977051.5451000035,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Ripple Llc","Title":"HAPTIX","City":"Salt Lake City","State":"UT","Abstract":"Develop neural interfaces to improve fine motor control and restore sense of touch and proprioception for prosthetics users.","FID":240}},{"geometry":{"x":-1.24553392711E7,"y":4977051.5451000035,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"University Of Utah","Title":"HAPTIX","City":"Salt Lake City","State":"UT","Abstract":"Develop neural interfaces to improve fine motor control and restore sense of touch and proprioception for prosthetics users.","FID":241}},{"geometry":{"x":-1.24553392711E7,"y":4977051.5451000035,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Utah","Title":"Collaborative Research: Analysis of the Mammalian Olfactory Code","City":"Salt Lake City","State":"UT","Abstract":"This project was developed during a NSF Ideas Lab on \"Cracking the Olfactory Code\" and is jointly funded by the Chemistry of Life Processes program in the Chemistry Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Physics of Living Systems program in the Physics Division, the Neural Systems Cluster in the Division of Integrative Organismal Systems, the Division of Biological Infrastructure, and the Division of Emerging Frontiers.<br /><br />The mammalian sense of smell is arguably the most complex sensory system in the animal kingdom. Hundreds of olfactory receptors are deployed to detect a vast array of chemicals with exquisite sensitivity in complex environments. This collaborative project combines biochemistry, neurobiology, genomics, mathematics and new technologies to understand how the mammalian olfactory system detects, encodes and extracts meaning from chemical stimuli. The goals of this project are to: (1) elucidate fundamental neural mechanisms for how chemical sensation turns into the perception of a smell; (2) produce a vast array of scientific resources to olfactory scientists; (3) provide valuable information for broader audiences, including for molecular evolution, chemical ecology, and flavor and fragrance communities; (4) establish new technologies and mathematical frameworks to study biological systems; and (5) facilitate applied chemical sensing technologies for environmental monitoring, food safety, and homeland security. The project also offers training opportunities from the high school to the postdoctoral trainee level, and educational opportunities and outreach through partnerships with local science museums as well as science learning centers and their media outlets.<br /><br />This project's efforts are organized around three aims that focus on how information about odor identity and odor valence (attractiveness/aversiveness) is encoded at the level of olfactory receptors (Aim 1); within the olfactory bulb, where odor information is first processed (Aim 2); and the cortical amygdala, where odor codes may integrate with other information streams (Aim 3). Completion of the project entails the development and use a broad array of innovative approaches that include mapping all human and mouse odorant receptors to the chemicals they bind, defining the innate valence of these chemicals using behavioral assays, mapping all odorant receptor projections to the olfactory bulb, functionally characterizing their neural representations in the olfactory bulb and cortical amygdala, and using novel mathematical approaches to understand the underlying structure of odor coding and olfactory neural circuits at the level of sensory neurons, olfactory bulb glomeruli, and amygdala. Progress towards each aim involves close collaborations between team members with diverse expertise, including molecular biology, behavioral neuroscience, in vivo functional imaging, and mathematical and theoretical analysis of complex datasets. The multidisciplinary strategy implemented here promises to lead to an integrated and comprehensive understanding of how mammals sense and make sense of their chemical environments.","FID":242}},{"geometry":{"x":-1.24553392711E7,"y":4977051.5451000035,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Utah","Title":"BRAIN EAGER: Danionella translucida: A New Fish Model for Systems Neuroscience","City":"Salt Lake City","State":"UT","Abstract":"Neuroscientists face the difficult task of describing the coordinated activities of many single neurons across the brain, and explaining how the cells' firing patterns create behavior. Achieving this goal at the immense scale of the human brain is the ultimate goal of the BRAIN Initiative. To accomplish this complex goal, it first is necessary to establish appropriate experimental and analytical techniques, as well as a better understanding of basic circuit principles, in simpler systems. The current project expands the opportunities for gaining insight by developing a new laboratory model organism. The candidate species is the fish Danionella translucida. This species is very small (~1 cm body length as an adult) and optically transparent, two characteristics that make the species exquisitely well-suited to molecular and optical techniques for recording from and manipulating large sets of neurons, and enabling researchers to use the most powerful experimental methods to study how each neuron in an adult vertebrate contributes to complex behaviors. The project will establish this potentially revolutionary model species and demonstrate proof-of-principle by mapping the neural circuits that underlie odor-mediated social alarm behavior in adult Danionella. The societal benefits of this work include unprecedented insight into the mechanisms of complex behaviors, some of which are affected in human neurological diseases. Additionally, the integration of multiple levels of analysis, from molecular biology to social behavior, render this project the basis of a particularly powerful neuroscience teaching tool, to be implemented through existing undergraduate and high school research programs that include outreach to students from minority groups. <br /><br />This project draws on Danionella's close phylogenetic similarity to the zebrafish, Danio rerio, to apply existing experimental tools to a new animal model. The first aim is to establish breeding, transgenesis, and gene editing techniques that will allow propagation of these fish in the lab, introduction of fluorescent reporters and optogenetic actuators, and targeted manipulation of specific, endogenous genes. The second aim is to apply multiphoton and light-sheet imaging to adult Danionella, and evaluate the results against benchmarks established in larval zebrafish. The third aim is to develop assays for a pheromone-mediated social alarm behavior, and record pheromone-evoked activity from every neuron in the brain. These experiments collectively demonstrate the experimental power of this new model species and create tools that are essential for its adoption by the research community. The insights will be disseminated through, among others, existing and new websites supporting exchange among scientists.","FID":243}},{"geometry":{"x":-1.24553392711E7,"y":4977051.5451000035,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Utah","Title":"US Ignite: Track 1: Remote Management of Deep Brain Stimulation (DBS) Patients Using Utah Telehealth Network (UTN)","City":"Salt Lake City","State":"UT","Abstract":"Deep brain stimulation (DBS) is a therapy that has been shown to be effective for the treatment of Parkinson's disease and essential tremor, and is now being assessed for a wide range of other disorders such as Alzheimer's disease, depression and traumatic brain injury. Hence, patients with a wide range of neurological disorders could benefit from DBS. However, these patients face an access problem because DBS devices are almost exclusively implanted and managed in major cities at academic medical centers. While it is reasonable for a patient to travel once or twice for surgery, it can be infeasible for them to travel long distances for post-operative management of their DBS devices in the months and years following surgery. We envision a new model in which patients travel once or twice for surgery and then are managed in their home area by community neurologists or family practice physicians who use expert decision support tools to choose DBS device settings. The purpose of this grant is to test the use of an app-based decision support platform that runs on iOS devices, and provides predictive, patient-specific computational models over a high-bandwidth network that was developed for healthcare applications. We believe that this system can drastically reduce the amount of time necessary for DBS programming, and in the future it may enable patients to be post-operatively managed without the need to travel to DBS surgical centers. We anticipate that if this study is successful then it will achieve a critical step by providing a system that runs on mobile devices, and can be used to manage DBS patients across a wide range of neurological disorders. Hence, we feel that the technology developed and tested in this application could have transformative effects on large numbers of patients.<br /><br />In recent years there has been substantial growth in the use of patient-specific computational models to predict and visualize the effects of neuromodulation therapies such as deep brain stimulation (DBS) to treat movement disorders including Parkinson's disease (PD) and essential tremor (ET). These models have been clinically validated, and their utility in DBS programming has been demonstrated in several studies. However, translating these models from a research environment to the everyday clinical workflow has been a major challenge, primarily due to the complexity of the models and the expertise required in specialized visualization software. In this application we propose to deploy an interactive visualization system, ImageVis3D Mobile (IV3Dm), which has been designed for mobile iOS computing devices such as the iPhone or iPad, to visualize patients-specific models of Parkinson's disease (PD) patients who received DBS therapy. Selection of DBS settings is a significant clinical challenge that requires considerable expertise to achieve optimal therapeutic response, and is often performed without any visual representation of the stimulation system in the patient. This issue is compounded by a catch-22 in the management of these patients: very few clinicians outside academic medical centers will manage DBS patients because they lack the tools and expertise to do so; no one has developed remote, mobile tools because there is a perception that providers outside academic medical centers will not use them. The purpose of this application is to break this deadlock by providing a decision support system that can provide clinicians with the tools necessary to manage DBS patients in rural areas. We have previously tested the utility of IV3Dm for programming DBS patients in a controlled clinical setting and have shown that it can drastically reduce the amount of time necessary to choose good therapeutic settings. In this application we proposed to add several key enabling technologies and test the use of IV3Dm on PD patients in remote areas of Utah. These include: integrating a previously developed GPU-based solver; adding remote volume rendering capability to IV3Dm to enable a wide range of possible DBS settings; testing IV3Dm over the Utah Telehealth Network (UTN), a broadband network in the State of Utah that is dedicated for use in healthcare. We anticipate that if this study is successful we will show that PD patients can receive care that is comparable to that provided by specialists at major medical centers but with far less patient burden (i.e. travel time). The intellectual merit of this application lies in the delivery of patient-specific computational models of DBS patients over a broadband telehealth network to improve the care of PD patients.","FID":244}},{"geometry":{"x":-1.24553392711E7,"y":4977051.5451000035,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Utah","Title":"EAGER: Implantable Particle-Based Wireless Neurorecording Probes for Minimally-Intrusive 3D Mapping of Brain Signals","City":"Salt Lake City","State":"UT","Abstract":"Proposal No:1550743: <br />EAGER: Implantable Particle-Based Wireless Neurorecording Probes for <br /> Minimally-Intrusive 3D Mapping of Brain Signals<br /><br />For the last thirty years neurorecording probe technologies have been implemented using arrays of needle like electrodes. The presence of needles in neural tissue causes extensive damage and inflammation that lead to scar tissue formation and eventual probe failure. This work proposes the use of electrodes arrays placed on the surface of sub-mm, instrumented spherical particles. The small, shank free particles thus allow for the healing of surrounding tissue after insertion minimizing scar tissue formation and extending probe life. This new technology has broad applicability in the realization of instrumentation for fundamental brain function studies, brain to machine interfaces and neural prostheses.<br /><br />The proposed work is divided into four separate tasks: (1) the development of new microfabrication technologies for construction of hollow, spherical micro-capsules with peripheral electrodes, (2) the development of ultracompact folded CMOS neurorecording circuits, (3) the development of compact RF biotelemetry circuits and (4) the testing of effectiveness, tissue damage and longevity of particle-based probes on small animals.","FID":245}},{"geometry":{"x":-1.24553392711E7,"y":4977051.5451000035,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Utah","Title":"NCS-FO: Imaging synaptic activity deep in the brain using super-resolution cannula microscopy","City":"Salt Lake City","State":"UT","Abstract":"Proposal # 1533611<br />Institute: University of Utah<br />Title: NCS-FO: Imaging synaptic activity deep in the brain using super-resolution cannula microscopy<br /><br />Objective: This project will develop a tool for high-resolution (<br /><br />Non-Technical <br />The long-term vision of this project is to image with high resolution deep inside the brain of freely moving mice using inexpensive technologies so as to elucidate the fundamental basis of information processing and memory. Changes in synaptic strength at specific synapses are thought to underlie memory encoding and storage, yet there is very little experimental evidence for this theory in the intact brain due to technical limitations of visualizing the specific synaptic pattern involved in experience-dependent learning. This project aims to overcome this limitation by transforming a simple, inexpensive cannula into a super-resolution fluorescence microscope. Commercialization of this technology will be pursued after the fundamental science and engineering has been demonstrated for widespread dissemination. <br /><br />Technical:<br />The objective of this proposal is to image neuronal activity, neuron structure and protein localization deep in the brain with sub-100nm resolution using computational cannula microscopy (CM) and novel molecular reporters of synaptic activity. CM will allow imaging of the brain in awake, freely moving animals at unprecedented spatial resolution. Current techniques in freely moving animals are limited to imaging the brain near the surface, include large and heavy head stages with moving parts, and cannot penetrate deep into the brain without significant damage to surrounding tissue. The ultimate goal of this proposal is to allow imaging of individual synapses in freely moving animals. We have already developed the framework for in vitro fluorescence imaging using CM. During this project, we will extend CM to enable: (1) super-resolution ( 1mm) with the vision of imaging activity and protein localization in individual synapses in the deep brain of freely moving animals. Changes in the strength of individual synapses are thought to underlie learning and memory in the brain, yet this fundamental theory of brain function lacks tangible experimental evidence to support it in vivo. Our project will enable studies that address the causal role of molecular events at individual synapses in mediating behavior and information processing.","FID":246}},{"geometry":{"x":-1.24553392711E7,"y":4977051.5451000035,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Utah","Title":"NCS-FO: Sensory-Motor Integration via Recording and Stimulating Arm Nerves","City":"Salt Lake City","State":"UT","Abstract":"Most ongoing research to develop advanced hand and arm prostheses that allow an individual with amputation to perform highly dexterous movements and to sense features of objects in the world has separated the performance of movements from the sensing of objects. However, in individuals with normal ability, sensory and motor information are integrated. This project's goal is to create movement and sensation abilities in individuals with amputation that are more similar to that in normally enabled individuals. In particular, the goal is to understand how to best utilize all of the available motor and sensory information in the design of accurate neural controllers for future generations of forearm prostheses. This integrated approach to creating sensory percepts and interpreting motor intent will recreate the natural, minimally monitored use of an artificial hand in volunteers as they interact with their world. Successful completion of the proposed work will begin the process of creating a prosthetic hand that passes the 'Turing Test,' where the user perceives little difference between the artificial hand and their amputated biological hand.<br /><br />The program of research involves implanting neural interfaces (for both stimulating and recording) in the major arm nerves of human volunteers and investigating use of these interfaces while the volunteers interact with a virtual world. In particular, the project has the goals of (a) identifying components in peripheral nerve signals that correlate with errors between the intended movement and the actual movement of the prosthetic arm; (b) developing accurate encoders and stimulation systems that provide punctate, naturalistic, multimodal, and graded sensory percepts; and (c) developing, characterizing, and evaluating advanced decoders that estimate movement intent from a combination of peripheral nerve signals and sensory information from the prosthesis. This third goal, an advanced decoder, will be evaluated with scenarios that provide a clear measure of performance and that represent activities of daily living. The integration of sensory percepts and motor intent is expected to create a natural, minimally monitored use of a prosthetic hand in order to interact more effectively with the world.","FID":247}},{"geometry":{"x":-8605983.9167,"y":4699035.180299997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"George Mason University","Title":"US-French Research Proposal: Collaborative Research: Spatial and Temporal Aspects of Molecular Signaling in Synaptic Plasticity","City":"Fairfax","State":"VA","Abstract":"The chemical, noradrenaline is released in many regions of the brain in response to anxiety and stress. Its action on brain cells in several regions contributes to memory storage and extinction, and in some circumstances memory of particularly stressful events creates problems such as post-traumatic stress disorder (PTSD). The hippocampus is one of the brain regions receiving noradrenaline and is an important locus of contextual memory. One mechanism whereby noradrenaline facilitates memory storage has been characterized, but PTSD treatments aimed at this mechanism has not been successful. Recently, a non-standard action of noradrenaline on brain cells was discovered, but the implications for memory storage have not been characterized. The proposed research will employ live cell imaging, physiology and computational modeling to investigate this alternative mechanism whereby noradrenaline modifies memory storage. The results will have major implications for the development of novel treatments for stress-related memory disorders, by suggesting novel molecular targets for pharmaceutical development.<br /><br />Noradrenergic signaling through &#946; adrenergic receptors (&#946;AR) crucially contributes to the long term synaptic plasticity (LTP) underlying memory storage in the hippocampus. Activation of noradrenergic receptors leads to elevations in the second messenger cAMP and the memory kinase PKA through classical signaling pathways. Recently a novel signaling pathway activated by &#946;AR, involving activation of the memory kinase ERK, has been shown to be involved in memory storage and synaptic plasticity. However, the mechanism employed in the hippocampus is not completely understood, which hinders development of novel treatments for stress-related memory disorders. Thus, the goal of this project is to delineate the role of &#946;AR signaling in the LTP underlying hippocampal memory storage. This research will define the role of ERK recruitment by &#946;2ARs in LTP, and demonstrate how different temporal patterns of stimulation use distinct signaling pathways downstream of &#946;2AR activation. The research uses computational spatial modeling of signaling pathways, live cell imaging in brain slice, electrophysiology, biochemistry, and molecular biology to demonstrate how different temporal stimulation patterns activate distinct signaling pathways downstream of &#946;2AR signaling. A back and forth interaction between live cell imaging of kinase activity and model development will produce an experimentally constrained and validated signaling pathway model. Then, simulation experiments will be used to design stimulation protocols that will be tested with electrophysiological and biochemical experiments. The research includes development of software tools (https://github.com/neurord/) to facilitate creation of models that help to interpret live cell imaging results.<br /><br />A companion project is being funded by the French National Research Agency (ANR).","FID":248}},{"geometry":{"x":-8605983.9167,"y":4699035.180299997,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"George Mason University","Title":"BRAIN EAGER: Building reliable high-throughput consensus for neuronal morphologies","City":"Fairfax","State":"VA","Abstract":"This EAGER project will provide all neuroscientists and computer scientists with much needed reliable, repeatable, high-throughput, quantitative data to begin piecing together the complex puzzle of the neural structure-activity-function relationship. Recent breakthroughs in genetic labeling and microscopic imaging have energized the research community with unprecedented optimism in the ability to collect the enormous amount of data that is necessary to quantify statistically representative samples of neurons in multiple species, developmental stages, and conditions, across the overwhelming variety of cell types throughout the nervous system. Due to the sheer extent and branching complexity of axonal and dendritic arbors, however, the bottleneck in the advancement of progress in this endeavor is no longer raw data acquisition, but the digital reconstruction of the corresponding morphology. The BigNeuron initiative (bigneuron.org) promises to consolidate and further advance the gains in automated tracing, and the ongoing development of multiple algorithms provides a strong insurance of robustness. Now, formulating a consensus from these alternative results is critical to prevent dispersive fragmentation and thrust the field into a new era of discovery.<br /><br />BigNeuron is porting all available algorithms for automated reconstruction of neuronal morphology under a unified open source framework. Each of the multiple BigNeuron algorithms will create non-identical digital tracings from every neuronal image stack. A remaining unsolved step is to morph these multiple variants into a single optimal consensus reconstruction that would de facto become a community standard. While human expertise is currently the gold standard (and the ground truth may not be known), even the reconstructions of the exact same neuron by two trained human operators will not be identical and need to be reconciled. Thus, to ensure scalable to whole-brain throughput, an automated method is needed to transform a collection of non-identical tracing versions into a consensus reconstruction, ideally with a confidence (or variance) associated with each branch. The specific aims of this project are to design, implement, test, refine, and deploy a method to generate a consensus neuronal reconstruction from the multiple digital tracings produced by each of the available algorithms. Specifically, the team will first create a draft working algorithm by synergistically combining two recently introduced complementary approaches. The resulting initial procedure for morphological consensus production will serve as straw man for community discussion in several meetings and workshops. After expert feedback and new ideas have been incorporated, the consensus generation process will be finalized for incorporation into the BigNeuron pipeline. Results from this project will be available to researchers and science educational users through the NeuroMorpho.Org website.","FID":249}},{"geometry":{"x":1.6135565283100002E7,"y":-4549016.0962000005,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Florey Institute Of Neuroscience And Mental Health","Title":"ElectRx","City":"Parkville","State":"VIC","Abstract":"Develop minimally invasive neurotechnologies for neuromodulation of organs and CNS structures to promote body's ability to heal itself.","FID":250}},{"geometry":{"x":-1.3595624876899999E7,"y":6053547.287199996,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"DARPA","Institution":"Roboti Llc","Title":"HAPTIX","City":"Redmond","State":"WA","Abstract":"Develop neural interfaces to improve fine motor control and restore sense of touch and proprioception for prosthetics users.","FID":251}},{"geometry":{"x":-1.3617651797699999E7,"y":6041154.5031,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Washington","Title":"BRAIN EAGER: Tuning the Intrinsic Computational Properties of Neurons to Changing Circuit Outputs during Early Brain Development","City":"Seattle","State":"WA","Abstract":"Neurons that are being formed in the brain of a developing animal send out electrical signals that spread like waves over large parts of the brain. The waves are essential for normal brain development. The goal of this project is to find out how this spontaneous electrical activity controls brain development. Recently, a specific type of neuron has been identified as being the pacemaker, or trigger, for these waves. This project will study how these neurons trigger the spontaneous waves. The project will take advantage of a mouse that allows these neurons to be stimulated using light. The responses of the neurons to these stimuli will be monitored, and the results will be used to make computer models of the neurons. These models will reveal the properties of these neurons that allow them to produce the waves. The project will offer opportunities for undergraduate and graduate students to be trained in interdisciplinary research that involves both theoretical and experimental biology, under the guidance of two collaborating principal investigators with unique expertise in these areas. Emphasis will be placed on actively recruiting women into full participation in the computational aspects of the project.<br /><br />This project investigates how the intrinsic electrical properties of developing GABAergic interneurons in the cerebral cortex allow them to initiate spontaneous waves of electrical activity during early development. Previous genetic and pharmacological data indicate that these neurons, which are excitatory during early development, are the primary pacemakers for waves of spontaneous activity in the mouse cortex between embryonic day 18 and and postnatal day 3. The detailed input:output relations of GABAergic neurons will be determined by using calibrated optical stimulation in a dlx5/6 channel-rhodopsin mouse and by recording the outputs of the neurons with extracellular electrode arrays. Conductance-based models of the neurons will be constructed that reflect the diversity of intrinsic properties that are encountered in the population. The model neurons will be connected into synaptic circuits to determine whether the measured properties lead to pacemaking activity in the circuit. By systematically varying the intrinsic properties in the model, aspects of the intrinsic properties that are critical for pacemaking function will be determined. If successful, this project will provide a new high-throughput method for determining how the intrinsic properties of neurons determine circuit output in the brain.","FID":252}},{"geometry":{"x":-1.3617651797699999E7,"y":6041154.5031,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"University Of Washington","Title":"Collaborative Research: The Ever-Changing Network: How Changes in Architecture Shape Neural Computations","City":"Seattle","State":"WA","Abstract":"Our brains are constantly changing. Experiences and memories leave their imprints on connections between neurons. Understanding this process is fundamental to understanding how the brain works. While this question has been of central importance to neuroscience for decades, at this moment researchers are well positioned to make significant progress -- new recording devices and imaging techniques are revealing the activity and changes within the networks of the brain at unprecedented scale and resolution. Sound mathematical models are essential to keep up with the mounting avalanche of data. The goal of this project is to develop mathematical tools to assist with improving understanding how networks of neurons are shaped by experiences. Developing this theory is crucial for understanding learning, as well as associated disorders. The project will focus on how learning improves the brain's ability to make decisions and store memories. Graduate students and postdocs joining this project will be part of an established, interdisciplinary mathematics research community. Trainees will gain a wide perspective of mathematical neuroscience through integrated research at three institutions, including extensive visits among them. <br /><br />This research project builds on earlier results of this team to address a central challenge in the mathematical analysis of biophysically realistic neuronal networks: How brain activity changes brain structure over time. Understanding neural computation demands a description of how network dynamics co-evolves with network architecture. The research team will address this challenge by answering specific questions about the interplay between spatiotemporal patterns of neural activity, the attendant changes in network architectures, and the resulting neural computations. This project focuses on two main questions. First, what mathematical techniques can describe the co-evolution of network dynamics and network connectivity toward stable assemblies of neurons? To address this question this project will build a theory describing how global network structure evolves under the dynamics of biophysically realistic plasticity rules that operate on the scale of individual spikes and synapses. Analysis of these models requires novel multiscale and averaging methods. The resulting equations allow analysis of the stability of network architectures and their dependence on stimulus drive. With these results, the second question can be addressed: How does network plasticity create spatiotemporal dynamics that support the basic building blocks of neural computation? Models to understand how plasticity forms networks whose dynamics underlie specific operations on incoming stimuli will be developed to address this question. The mechanism by which long-term plasticity can reshape the connectivity of a network to encode a precise temporal sequence of events will also be investigated.","FID":253}},{"geometry":{"x":-9177776.2146,"y":4638903.473200001,"spatialReference":{"wkid":102100,"latestWkid":3857}},"attributes":{"Agency":"NSF","Institution":"Marshall University Research Corporation","Title":"RUI: Biological Engineering of Neural Migratory Streams","City":"Huntington","State":"WV","Abstract":"PI: Price, Elmer M. <br />Proposal Number: 1511928<br /><br />Recent evidence indicates that there exist locations in the adult brain that constantly generate new cells that migrate into specific regions involved in olfaction, memory and learning. This project aims to provide new information regarding the mechanisms that are responsible for this important and complex process. The PI also plans to use this knowledge to bioengineer structures which, when implanted into brain, will form new migratory paths that will deliberately target new neurons into specific regions of the brain. When delivered to areas impacted by injury or disease, these new neurons are anticipated to restore lost function.<br /><br />During adult neurogenesis, a large number of molecules participate in complex signaling, which requires precise spatial and temporal control. Although several of these neurotrophic ligands and cognate receptors have been identified, many questions remain regarding the molecular mechanisms by which these components function. The goals of this project are to characterize the mechanism by which specific factors mediate neurogenesis using an in vitro system and then use this information to bioengineer cylindrical fibrin-based implants which will generate new neural migratory paths in vivo. The project involves in vitro and complementary in vivo aims. The premise of the in vitro studies is that neural stem cells receive neurotrophic signals in a particular order and one role of each ligand is to induce the expression of the receptor for the next ligand. The in vivo experiments will exploit novel, readily bioengineered fibrin cylinders that will be implanted into the brain in order to recruit endogenous neural progenitor cells from their usual niche and target them into non-neurogenic regions. The project will use time-lapse microscopy, fluorescence microscopy, immunochemistry, and animal behavioral studies to accomplish the aims. Undergraduate researchers will participate in this research through a program dubbed FIRE (Full Immersion Research Experience), where the students will be involved in all aspects of a research program, including literature evaluation, grant writing, technical and presentation skill development, and preparation for graduate school 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