Funded Awards

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Title Investigator Institute Fiscal Year FOA Number Status Project Number Priority Area Summary
3D neonatal Photoacoustic Tomography (3D-nPAT) to detect Hypoxic-Ischemic brain injury in preterm neonates Nasiriavanaki, Mohammadreza Wayne State University 2019 Active
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity

Hypoxic-ischemic brain injury (HII) is a severe condition caused by a lack of oxygen to the brain at or near the time of birth in preterm and low birth weight newborns. Unfortunately, there is a lack of high quality, non-invasive imaging technologies that allow for bed-side imaging of brain hypoxia and monitoring of early brain development in newborn children. Dr. Nasiriavanaki and colleagues will develop a novel, portable, point-of-care 3D neonatal photoacoustic tomography (3D-nPAT) system to detect hypoxic ischemic brain regions in preterm neonates. Unlike current imaging options, this technology will not require sedation, radiation, or radionuclides. 3D-nPAT aims to provide an accurate 3D map of brain tissue oxygen levels within the neonatal cranium, which will improve the diagnostic information of HII.

4D Transcranial Acoustoelectric Imaging for High Resolution Functional Mapping of Neuronal Currents Witte, Russell S (contact) University Of Arizona 2019 Active
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity

Achieving high spatiotemporal resolution with non-invasive electrophysiology measurements continues to be a challenge for human neuroscience. One promising method is transcranial acoustoelectric brain imaging (tABI), which uses an ultrasound beam to safely and briefly alter brain tissue conductivity. The rapid detection of these modulations overcomes limitations in conventional electroencephalography that can result in signal blurring. Here, Dr. Witte and a multidisciplinary team of investigators aim to develop, validate and implement tABI for noninvasive functional mapping of neural currents deep in the human brain through the skull. The success of this approach would demonstrate a safe and revolutionary modality for mapping brain electrical activities, enabling future work to transform our understanding of brain function.

A 5-dimensional connectomics approach to the neural basis of behavior KATZ, PAUL UNIVERSITY OF MASSACHUSETTS AMHERST 2018 Active
  • Integrated Approaches

The brain is constantly assessing information that guides decision making, which can be a matter of life or death. For example, animals can choose to go to a place filled with food or an area filled with predators. Dr. Katz and his team will examine how neural circuits allow the mollusk Berghia stephaniaedecide where to go, implementing this common decision behavior with fundamental, reductionist neural mechanisms. The group will start by creating a complete map of the Berghia nervous system, which will detail connections between neurons and sensorimotor structures, as well as gene expression in the cells, before exploring the cells and circuits involved in decision making related to navigation. This project will provide a new animal model for studying the nervous system in fundamental simplicity and will offer a broader understanding of the decision-making processes in more complex brain structures.

A Brain Circuit Program for Understanding the Sensorimotor Basis of Behavior Clandinin, Thomas Robert Dickinson, Michael H (contact) Druckmann, Shaul Mann, Richard S Murray, Richard M Tuthill, John Comber Wilson, Rachel California Institute Of Technology 2017 Active
  • Integrated Approaches
The coordination amongst components of the central nervous system to guide sensorimotor behavior requires an understanding of exactly how these modules interact, from low-level transmissions guiding individual muscles, to high-level communications for complex behavior. Michael Dickinson and a multi-disciplinary team of experts will develop a theory of Drosophila fruit fly behavior that incorporates neural processes and feedback across hierarchical levels, using methods developed from their prior BRAIN effort. Here, the team plans to use synergistic approaches – genetics, electrophysiology, imaging, biomechanics, behavior analysis, and computational methods – to understand feedback and the flow of information within and across different processing stages in the awake, intact fly brain. By investigating these hierarchical levels with parallel approaches, this project has the potential to provide a fundamental synthesis of how the central nervous system generates behavior.
A BRAIN Initiative Resource: The Neuroscience Multi-omic Data Archive White, Owen R University Of Maryland Baltimore 2017 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

A thorough understanding of the complexities of the brain’s different cell types requires the sharing and integration of myriad genomic information generated from various data sources. Owen White proposes creating a Neuroscience Multi-Omic (NeMO) Archive, a cloud-based data repository for -omic data. White and his team of researchers will establish an archive for multi-omic data and metadata of the BRAIN Initiative. The group will document and archive data processing workflows to ensure standardization, as well as create resources for user engagement and data visualization. The NeMO Archive will provide an accessible community resource for raw -omics data and for other BRAIN Initiative project data, making them available for computation by the general research community.

A Confocal Fluorescence Microscopy Brain Data Archive Bruchez, Marcel P Ropelewski, Alexander J (contact) Watkins, Simon C Carnegie-mellon University 2017 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

Advances in microscopy and imaging have created new possibilities in many fields of research, but these advances have also generated large amounts of data that can overwhelm traditional data management systems. Along with collaborators at Carnegie Mellon University and the University of Pittsburgh, Alexander Ropelewski plans to establish a BRAIN Imaging Archive that takes advantages of infrastructure and personnel resources at the Pittsburgh Supercomputing Center. The Archive will include a pipeline for data submission, user access and support, and BRAIN Initiative community engagement through an online presence, workshops, and hackathons. This unique resource will provide an accessible and cost-effective way for the research community to analyze, share, and interact with large image datasets of the BRAIN Initiative.

A data science toolbox for analysis of Human Connectome Project diffusion MRI Rokem, Ariel Shalom University Of Washington 2019 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

The Human Connectome Project provides one of the largest publicly available datasets of diffusion MRI from a sample of healthy individuals. Dr. Rokem and team will create an end-to-end pipeline for analysis of human white matter connections by using “tractometry” methods to analyze the diffusion MRI dataset from the Human Connectome Project. In tractometry, tissue properties are estimated in the long-range connections between remote brain regions. This project aims to generate a normative distribution of tissue properties in the major white matter connections, develop novel statistical methods to connect the properties of white matter connections to cognitive abilities, and create visualization tools to further explore and communicate the data. These tools may create an easily accessible platform that could be applied to other important neuroscience datasets.

A Facility to Generate Connectomics Information Lichtman, Jeff HARVARD UNIVERSITY 2018 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

Connectomics describes a field of study that builds maps of the connections within the brain. Dr. Lichtman and colleagues have developed a facility for generating high-resolution, large-volume serial section electron microscopy data that can be used to generate connectomic maps. In this project, access to the facility, techniques, and analytical software will be provided to the broader neuroscience community. This will allow other research groups who may be inexperienced in these techniques to generate data in projects aimed at mapping brain circuitry, a high priority goal in the BRAIN 2025 report. By providing this resource, Dr. Lichtman and colleagues will help researchers classify the cell types within healthy and diseased brains or model systems, which will improve our understanding of brain function and neurological disorders.

A Fast, Accurate and Cloud-based Data Processing Pipeline for High-Density, High-Site-Count Electrophysiology Kimmel, Bruce VIDRIO TECHNOLOGIES, LLC 2018 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

The community’s need for an integrated open-source analysis platform is rapidly growing due to the increasing capacity of extracellular electrodes and the limited number of new and validated spike- sorting methods. JRCLUST, a free, open-source, standalone spike sorting software, offers a scalable, automated and well-validated spike sorting workflow for analysis of data generated by large multielectrode arrays. The software can tolerate experimental recording conditions from behaving animals, and it can handle a wide range of datasets using a set of pre-optimized parameters making it practical for wide use in the community. JRCLUST has been adopted in 20+ labs worldwide since its inception less than a year ago. Drs. Kimmel and Nathan seek to expand and maintain JRCLUST, thus empowering researchers to elucidate how functionally defined subpopulations of neurons mediate specific information-processing functions at key moments during behavior.

A genetically Encoded Method to Trace Neuronal Circuits in the Zebrafish Brain Lois, Carlos Prober, David Aaron (contact) California Institute Of Technology 2019 Active
  • Integrated Approaches

A goal of the BRAIN Initiative is to help researchers map out complete wiring diagrams of neural circuits. Recently the Prober and Lois group developed an approach called TRACT (Transcellular control of transcription) which allows researchers to map out and genetically manipulate the activity of neural circuits in Drosophila. However, it is difficult to study complex behaviors in these animals. In this project, the Prober and Lois groups plan to tailor the TRACT system for zebrafish, a vertebrates and that is easier for scientists to work with when studying complex behaviors. Their results may help scientists study, in great detail, how neural circuits control behavior under healthy and disease conditions.

A high-performance unshielded wearable brain-computer interface based on microfabricated total-field OPMs Contreras-vidal, Jose Luis (contact) Knappe, Svenja University Of Houston 2018 Active
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity

Non-invasive imaging methods, such as magnetoencephalography (MEG), are powerful in their ability to image brain dynamics without contacting the skull and scalp, but MEG is limited by the requirement of a magnetic shielding environment. In this proof-of-concept project, Drs. Jose Contreras-Vidal, Svenja Knappe, and a team of investigators will develop a wearable, compact, and noninvasive MEG system that can operate without external shielding, while maintaining high performance. The group will then validate the prototype system in a small-scale human study through a closed-loop MEG-based brain-computer interface system. The successful creation of a wearable MEG system will enable behaviorally active human neuroimaging that allows flexible movement in time and space, while providing high-quality sensitivity to neuronal sources.

A magnetic particle imager (MPI) for functional brain imaging in humans Wald, Lawrence L Massachusetts General Hospital 2017 Active
  • Monitor Neural Activity
  • Interventional Tools
  • Integrated Approaches
  • Human Neuroscience
A complete understanding of human brain network structure and functional activation requires non-invasive imaging tools that generate high-resolution functional maps with dramatically increased sensitivity. Lawrence Wald and his team believe that achieving the next level of sensitivity of neuroimaging technology will occur through functional magnetic particle imaging (MPI). Unlike functional magnetic resonance imaging (fMRI) which indirectly detects blood oxygenation level, fMPI can directly detect this iron concentration with no intermediate step. Because MPI shares a technological foundation with MRI, the researchers can validate the fMPI method in animals and human simulations before assessing its sensitivity in humans. The development of fMPI could provide brain function information over an order of magnitude more sensitive than fMRI.
A Neural Systems Approach to Understanding the Dynamic Computations Underlying our Sense of Direction Taube, Jeffrey Steven (contact) Van Der Meer, Matthijs Dartmouth College 2019 Active
  • Integrated Approaches

How do you find your way around? Navigation relies on a variety of information points such as self-motion and visual landmarks, which help with our sense of direction. Using large-scale recordings, live calcium imaging, and modeling data, Dr. Taube’s group will examine where direction-related information comes from and how the brain puts it all together to determine where an animal is and where it needs to go. This project will improve understanding of how the brain collects information from the eyes, head, and body and combines it with visual landmarks to determine head direction.

A novel optically pumped magnetometer (OPM) system for high resolution magnetocorticography Nugent, Allison C. (contact); Robinson, Stephen E. U.s. National Institute Of Mental Health 2019 Active
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity

Magnetoencephalography (MEG) is a non-invasive imaging technology that measures the magnetic field outside the head produced by electrophysiological activity in the brain. Currently available MEG systems, which are based on superconducting quantum interference devices (SQUIDs), often lack spatial resolution because the sensors cannot be placed directly on the scalp. Drs. Nugent, Robinson, and team will develop a new system based on an optically pumped magnetometer (OPM) for non-invasive human brain imaging.  By minimizing the standoff distance, this new magnetocorticography technology will be capable of providing millimeter resolution mapping of cortical brain function in healthy and diseased brains.

A Technology Resource for Polymer Microelectrode Arrays Meng, Ellis (contact); Song, Dong University Of Southern California 2019 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

Polymer microelectrode arrays are electrical recording devices made of flexible materials. These materials reduce tissue damage and improve the long-term stability of the recording setup. The Meng and Song labs aim to establish a service that will manufacture and test out arrays that are customized to researchers’ needs. The service may help researchers use the latest electrical recording devices for studying a variety of neurological disorders.

A TOF, DOI, MRI compatible PET detector to support sub-millimeter neuroPET imaging Dolinsky, Sergei Miyaoka, Robert S (contact) University Of Washington 2018 Active
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
Currently, body imaging systems perform brain imaging, making it difficult to provide the necessary level of spatial and temporal resolution needed to understand brain function. Brain-only imaging systems include positron emission tomography (PET) and are referred to as neuroPET. Drs. Robert Miyaoka, Sergei Dolinsky, and a team of investigators seek to develop improvements in both image resolution and signal-to-noise ratio of neuroPET technology. The researchers will characterize neuroPET parameters, validate them through machine learning methods, and characterize performance of a prototype detector that is compatible with magnetic resonance imaging (MRI). By improving detector imaging technology that facilitates compatibility between PET and MRI, this work will improve image resolution to advance research into the development, function, and aging of the human brain.
A unified cognitive network model of language Crone, Nathan E Tandon, Nitin (contact) University Of Texas Hlth Sci Ctr Houston 2016 Active
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
Current non-invasive methodologies limit our ability to understand the neural basis of cognitive processes due to poor temporal or spatial resolution, and typical intracranial EEG (icEEG) approaches provide fragmentary information. To address these limitations, Drs. Tandon and Crone will study human language function, working with epilepsy patients who have intracranial electrodes in place. The group will then modulate activity at identified nodes of brain activity using closed-loop direct cortical stimulation. This project could provide insight into language processing and organization in the brain using a novel method of modeling neural computation, and provide insight into the language impairments that can affect patients with a range of neurologic and psychiatric illnesses.
A unified framework to study history dependence in the nervous system Santamaria, Fidel University Of Texas San Antonio 2019 Active
  • Integrated Approaches
  • Theory & Data Analysis Tools

A central property of the nervous system is history dependence: its ability to change reaction rates based on previous activity. Though the phenomenon is prevalent across scales of neuronal organization, sensory modalities, and species, there is no unified theory for history dependence. For this project, Dr. Fidel Santamaria and team will apply mathematical approaches to history dependence, validate the significance of that approach, and establish collaborations to test the hypothesis across species and scales. Overall, this project aims to provide a unified theoretical framework and in doing so, pave the way toward applications to study, analyze, and design experiments of history-dependent neuronal activity across multiple scales, from synaptic plasticity to complex spiking patterns in neural networks.

A wearable functional-brain-imaging system with full-head coverage and enhanced spatiotemporal-resolution to study complex neural circuits in human subjects Schwindt, Peter D. D. Sandia Corp-sandia National Laboratories 2019 Active
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity

Comprehensively studying the brain requires non-invasive neuroimaging methods at high spatiotemporal resolution that can capture the functions in naturalistic behaviors. Magnetoencephalography (MEG) is a promising approach, but its operation uses rigid helmet hardware that compromises signal and spatial resolution. Dr. Schwindt and a team of investigators plan to address these challenges by improving MEG sensors to develop a wearable, conformable, full-head coverage MEG system. After developing the sensor array, the group aims to enhance spatial resolution of the MEG system while accounting for heterogeneity in head shape, and finally validate the performance of the new system against traditional approaches. By providing a whole-head MEG system for people of all head sizes, this advance will enable the study of brain dynamics in increasingly naturalistic environments with cortical spatial resolution rivaling functional MRI.

Accurate and reliable computational dosimetry and targeting for transcranial magnetic stimulation Gomez, Luis Javier Duke University 2019 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

Transcranial magnetic stimulation (TMS) is a noninvasive technique used to study brain function and can be used to treat some brain disorders. Researchers use computational simulations of TMS electrical fields to gain a better understanding of how TMS affects the brain. Existing simulations, however, are inherently variable due to factors that impact the accuracy and precision of the technique, such as differences in experimental set-up and coil placement. Dr. Gomez proposes to use a novel computational framework to measure and address the uncertainty and variability of TMS electrical fields. The project will increase the fidelity and reliability of TMS simulations. The results will benefit researchers and clinicians by enabling more precise control of the technique and may help improve medical uses of TMS.

Achieving ethical integration in the development of novel neurotechnologies Chiong, Winston University Of California, San Francisco 2017 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools
Novel neurotechnologies hold promise for treating neuropsychiatric disorders, but also raise profound neuroethics issues including self-ownership of our thoughts, emotions, and actions. Engaging patients and researchers in the early stages of neurotechnology research and clinical translation can help ensure ethical development of the field. This research study will be embedded in one of two projects funded by the DARPA BRAIN Initiative to develop implantable brain stimulation devices that both monitor and adaptively stimulate brain areas involved in mood and behavior regulation. Dr. Chiong and an interdisciplinary team with expertise in neuroscience, clinical care, law, philosophy, and social science will assess neuroethics issues associated with the DARPA-funded brain stimulation project. The overall goal is to enable acceptability and adoption of new treatments for neuropsychiatric disorders, by recognizing and incorporating the perspectives of patients, researchers, and other stakeholders into the design of these novel neurotechnological therapies.
An open software solution to integrate non-invasive brain stimulation with functional imaging data Opitz, Alexander University Of Minnesota 2019 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

Non-invasive brain stimulation methods, like transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), and transcranial alternating current stimulation (tACS), modulate brain activity in a safe and painless manner. Several BRAIN Initiative projects are combining these non-invasive brain stimulation methods with neuroimaging methods. Dr. Opitz and team will develop a computational tool that integrates empirically validated finite element method (FEM) models with imaging data, by extending and scaling the SimNIBS (Simulation of Non-Invasive Brain Stimulation) software platform. The SimNIBS is the leading open source software platform for generating FEM-based models of the electric field distribution produced by TMS, tDCS, and tACS. The resultant analysis package will allow rapid visualization and analysis of non-invasive brain stimulation (NIBS) BRAIN Initiative data, which could be more broadly used by the general neuroscience community.

Assessing the Effects of Deep Brain Stimulation on Agency Roskies, Adina L Dartmouth College 2018 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

Deep brain stimulation (DBS), a method of modulating brain circuit function, is FDA-approved for certain brain disorders such as Parkinson’s Disease. The NIH BRAIN Initiative aims to launch neurotechnological developments that include new ways of directly affecting brain circuit function. Use of these novel interventions warrants careful consideration about ways in which brain stimulation may affect personal identity, autonomy, authenticity and, more generally, agency. In this project, Dr. Roskies and her team will develop an assessment tool to measure changes in agency due to direct brain interventions, and establish a database to catalogue these changes in agency in various patient populations receiving DBS. These efforts have the potential to facilitate improvements in therapeutic approaches and informed consent and will be used to develop a framework for further neuroethical thought about brain interventions, allowing us to better identify, articulate, and measure effects on agency.

Bayesian estimation of network connectivity and motifs Ringach, Dario L University Of California Los Angeles 2016 Active
  • Integrated Approaches
  • Theory & Data Analysis Tools
Learning how emergent behavior arises from single neurons is a key challenge in modern neuroscience. Ringach and his colleagues plan to create sophisticated algorithms and methodologies to derive the functional connectivity of neurons based on activity patterns at the single-cell level and then identify collections of neurons, or network motifs, that play important computational roles in network functions. The researchers will then validate their algorithms against a database combining functional calcium imaging data with “ground truth” estimates of direct synaptic connectivity. These tools and validation data will enable the investigation of how network motifs differ in both health and disease states.
BCI2000: Software Resource for Adaptive Neurotechnology Research Brunner, Peter Schalk, Gerwin (contact) Wadsworth Center 2019 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

Changes occur to the central nervous system (CNS) throughout life due to activity-dependent plasticity as we learn new behaviors. Adaptive neurotechnologies are systems that can interact with the CNS in ways that produce beneficial neural plasticity. The group led by Schalk and Brunner has created a software platform, BCI2000, that can be used in a variety of adaptive neurotechnology applications. However, the current BCI2000 system requires considerable expertise in programming for successful implementation. This project will produce a configuration of BCI2000 that can be more easily used for adaptive neurotechnology experiments, as well as an introductory course and online training for scientists, engineers, and clinicians using the system. These new resources will allow deployed neurotechnologies to be more quickly used in the study, diagnosis, and treatment of brain disorders.

Behavioral readout of spatiotemporal codes dissected by holographic optogenetics Rinberg, Dmitry (contact) Shoham, Shy New York University School Of Medicine 2014 Complete
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  • Monitor Neural Activity
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Dr. Rinberg's team aims to understand how the brain turns odors into nerve signals by activating and recording neurons in the olfactory bulbs of mice as they detect a variety of odors.
Behavioral state modulation of sensorimotor processing in cerebellar microcircuits Heiney, Shane A Baylor College Of Medicine 2017 Active
  • Integrated Approaches
Behavioral states affect sensorimotor processing, as sensory signals are converted into motor commands. Because these transformations are often distributed throughout the brain, it is challenging to understand the contributions of individual brain areas. Shane Heiney and colleagues are investigating how locomotion and arousal – two well-characterized behavioral states – subsequently affect cerebellar processing in mice. Using a combination of psychophysics, large-scale multiphoton imaging, and electrophysiology, Heiney plans to develop a quantitative framework for interpreting effects of behavior on cerebellar circuitry, and to study the impact of behavior on skilled movements at multiple stages of sensorimotor processing. These experiments have the potential to illuminate how a neural system and behavioral state are dynamically modulated in time.
Beyond Diagnostic Classification of Autism: Neuroanatomical, Functional, and Behavioral Phenotypes Fletcher, Preston Thomas University Of Utah 2016 Active
  • Integrated Approaches
  • Theory & Data Analysis Tools
A major barrier to creating effective treatments for autism spectrum disorder (ASD), a lifelong neurological disorder characterized by stereotyped behavior and difficulties in social interactions, is the lack of understanding of the underlying brain mechanisms. Fletcher and his team propose to develop novel statistical methods for integrating the analyses of neuroimaging data (functional and structural MRI) with behavioral assessments. The resulting set of open-source tools will help relate brain networks to specific ASD behaviors, as well as those observed in other neuropsychological disorders.
BIDS-Derivatives: A data standard for derived data and models in the BRAIN Initiative Poldrack, Russell A Stanford University 2017 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
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  • Monitor Neural Activity
  • Theory & Data Analysis Tools

The proliferation and heterogeneity of magnetic resonance imaging (MRI) experiments, data analysis pipelines, and statistical modeling procedures presents a challenge for effective data sharing and collaboration. Russell Poldrack and colleagues propose expansion of the Brain Imaging Data Structure (BIDS), which standardizes the description and collection of imaging data/metadata for MRI, with development plans for other neuroimaging types as well. Under BIDS, the group will develop standards for pre-processing data pipelines, computational modeling results, and statistical modeling, using quick validation of any implemented standard so that researchers can assess whether their data fit within BIDS guidelines. These standardization goals will facilitate sharing of data, modeling, and results, ensuring their usability and engaging the greater research community in developing highly useable data standards.

Boss: A cloud-based data archive for electron microscopy and x-ray microtomography Wester, Brock A. Johns Hopkins University 2018 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
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  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

Technological advancements in high-resolution imaging of brain volumes permits the accumulation of huge quantities of data that requires solution for storage and archiving. Dr. Brock’s project develops an open, accessible, and cloud-based data archive for electron microscopy and X-ray microtomography data by leveraging the proven architecture of the existing BossDB database. Allowing for petabyte scale data storage, curation, sharing, visualization and analysis, the archive is scalable and allows for a fast in- memory spatial data store, seamless migration of data between low cost and durable object storage (i.e. S3), and rapid access to the enormous datasets. The system enables computing data quality metrics on large datasets and metadata stores through a standardized interface. The archive is developed through an agile process that actively folds in community stakeholders for regular reviews and continuous opportunities for design input.

BRAIN INITIATIVE RESOURCE: DEVELOPMENT OF A HUMAN NEUROELECTROMAGNETIC DATA ARCHIVE AND TOOLS RESOURCE (NEMAR) Delorme, Arnaud Majumdar, Amitava Makeig, Scott (contact) Poldrack, Russell A University Of California, San Diego 2019 Active
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  • Human Neuroscience
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Dr. Makeig et al. have identified the need for the creation of data archives and standards for specifying, identifying, and annotating the data deposited. Specifically, they aim to create a gateway from the OpenNeuro.org archive for human neuroelectromagnetic data such as EEG and MEG data. This gateway will also provide tools to users for quality evaluation and data visualization. This resource will further allow machine learning methods to be applied to human brain activity data.

BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain Chung, Moo K University Of Wisconsin-madison 2016 Complete
  • Integrated Approaches
  • Theory & Data Analysis Tools

To what extents are structural and functional brain networks the product of heritability? That is the question that Chung and his colleagues will address with their proposal to develop tools to analyze in detail brain imaging scans (MRI, functional MRI, diffusion tensor imaging) they have collected from 200 pairs of monozygotic and same-sex dizygotic twins. The tools will be part of a new open-source suite of algorithms for analyzing their enormous cache of neuroimaging data, which the researchers will use to establish a baseline map for the genetic influences on brain network development in both health and disease.

BRAIN power: expanding reproducibility, quality control, and visualization in AFNI/SUMA COX, ROBERT WILLIAM (contact); NIELSON, DYLAN MILES U.S. NATIONAL INSTITUTE OF MENTAL HEALTH 2018 Active
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  • Human Neuroscience
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AFNI (Analysis of Functional NeuroImages) is an open-source software package for neuroimaging analysis and visualization of both functional and structural MRI as well as other modalities. Drs. Cox and Nielson propose to extend this widely used software package by offering containerization, cloud accessibility and web-accessible visualization. The software extension could support evolving BRAIN Initiative standards for human neuroimaging data organization and experiment specification. The project makes it possible for public integration testing of the software package, thus enabling end-user feedback and wider adoption and dissemination within the neuroimaging community.

Breaking Spatiotemporal Barriers of MR Imaging Technologies to Study Human Brain Function and Neuroenergetics Chen, Wei (contact) Zhu, Xiao-hong University Of Minnesota 2018 Active
  • Human Neuroscience
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  • Interventional Tools
  • Monitor Neural Activity

Advancing the image sensitivity and resolution of magnetic resonance (MR) imaging technologies is fundamental towards capturing a comprehensive view of the healthy human brain. Dr. Wei Chen and colleagues propose the development and validation of radiofrequency (RF) coil technology, combining it with spatiospectral CorrElation (SPICE) technique to improve the quality of MR imaging (MRI) and MR- spectroscopic imaging (MRSI) for human brain studies. Their approach aims to improve image sensitivity, while minimizing absorption of RF power in neural tissue, as well as exploit their previously developed SPICE technique to boost signal-to-noise ratio and image resolution. By pioneering this neuroengineering solution to improve the quality and resolution of these MR imaging technologies, these researchers will enable ultrahigh-resolution mapping of neural activity, circuits, and dynamics.

Breaking the Barriers to Microscale fMRI Vu, An Northern California Institute 2019 Active
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity

The need for improved non-invasive imaging is paramount in order to reveal the underpinnings of both the diseased and healthy human brain. Dr. Vu and colleagues will develop a Stimulus-Locked K-Space (SLIK) approach to achieve meso-resolution imaging for whole human brain fMRI. They will incorporate and evaluate commercially available motion mitigation and navigator-based dynamic B0 correction techniques. This novel technology will build upon existing commercialized 7 Tesla scanners, and therefore, following its development, could be readily disseminated to the neuroscience community.

Bridging structure, dynamics, and information processing in brain networks Choi, Hannah University Of Washington 2019 Active
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  • Human Neuroscience
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The mammalian brain has unique abilities to process various sensory inputs from the environment, based on efficient and complex brain network structures and dynamics. However, the precise connections between the brain’s intricate wiring and its rich network dynamics are unclear, as is our understanding of how the brain’s connectivity and dynamics relate to underlying neural coding principles. Leveraging the Allen Institute’s Mouse Brain Connectivity Atlas, Dr. Choi will explore these issues, ultimately aiming to help close the gap between brain biophysiology and neural coding principles, with a focus on predictive coding theory using data-driven mathematical models.

Building a Complete, Predictive, Data-Driven Model of Action Selection During Olfactory Navigation Louis, Matthieu R. P. J. C. G. University Of California Santa Barbara 2019 Active
  • Integrated Approaches

We still do not understand fully how animals process sensory inputs from a noisy environment, yet this is a crucial function that the nervous system must perform to make correct behavioral decisions. Dr. Louis and colleagues propose to create a model of how the nervous system converts noisy sensory information into something that can be used to navigate the environment. Specifically, they are studying the behavior of fly larvae and their response to olfactory inputs,  i.e. their attraction to food odors, to study how environmental inputs are processed in the brain. This information will then be tested to uncover how stimuli from a noisy environment is translated into behavioral decisions.

Building analysis tools and a theory framework for inferring principles of neural computation from multi-scale organization in brain recordings Sommer, Friedrich T University Of California Berkeley 2018 Active
  • Integrated Approaches
  • Theory & Data Analysis Tools

Innovative recording techniques have uncovered interactions between individual neurons and cell populations that comprise complex and poorly- defined neural dynamics underlying computations and brain functions. Dr. Sommer proposes combining new tools to analyze this neuronal activity with a theoretical framework of the associated computations. After decoding behavior in mice from hippocampal recordings during exploration and replay and local field potentials from visual cortex, the group will extract “place components” or the position of the animal from the activity data. Subsequently, the team will establish a theoretical framework that, at the computational level, will describe computations underlying brain function in terms of high-dimensional representations, and at the mechanistic level will describe how the operations and representations are mapped onto biological mechanisms. Future users will be able to use this framework to design computations, explore multiple potential mechanisms, create a simulation of an experiment, and compare simulation data to a real experiment.

C-PAC: A configurable, compute-optimized, cloud-enabled neuroimaging analysis software for reproducible translational and comparative Craddock, Richard Cameron Milham, Michael Peter (contact) Child Mind Institute, Inc. 2018 Active
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  • Human Neuroscience
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Novel neuromodulation, recording, and imaging techniques applied to human and non- human primate brains generate datasets that require tools for organizing, processing and analyzing data that are widely available and easy to use. Drs. Milham and Craddock plan to extend C-PAC (Configurable Pipeline for the Analysis of Connectomes), building a configurable data analysis pipeline that incorporates various statistical analysis, machine learning, and network analytic techniques. In addition to adapting methods used in human imaging for non-human primate data, the project will implement a toolbox for alignment of electrophysiological data with brain imaging data. The resulting software enables high- throughput, semiautomated and end-to-end processing and analysis of structural and functional MRI data that are accessed locally or via the cloud.

Canonical computations for motor learning by the cerebellar cortex micro-circuit Brunel, Nicolas Hull, Court A Lisberger, Stephen G (contact) Medina, Javier F Duke University 2019 Active
  • Integrated Approaches

The cerebellum plays critical roles in learning and performing coordinated, well-timed movements. The majority of research on the cerebellum has focused on Purkinje cells. This project aims to use optogenetics, machine-learning, electrophysiology, imaging, and computer modeling to investigate the entire cerebellar circuit including all relevant cell types to gain a better understanding of how the cerebellum functions to support motor learning.

Causal mapping of emotion networks with concurrent electrical stimulation and fMRI Adolphs, Ralph (contact) Howard, Matthew A. Poldrack, Russell A California Institute Of Technology 2018 Active
  • Human Neuroscience
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  • Monitor Neural Activity
Limited treatment options exist for emotional disorders because we do not understand the neural systems by which emotions are processed. Adolphs and colleagues will study how emotion is caused  by activity in brain networks. They will electrically stimulate emotion-related brain regions, such as the amygdala, in awake neurosurgical patients, and use concurrent fMRI to image the whole-brain networks engaged by the stimulated structures. Psychophysiological, behavioral, and self-report measures of emotion will be collected to quantify how the stimulation-induced activation patterns associate with specific components of emotion. This work could inform interventions to treat mood disorders through deep-brain stimulation.
Chemogenetic Dissection of Neuronal and Astrocytic Compartment of the BOLD Signal Shih, Yen-yu Ian Univ Of North Carolina Chapel Hill 2016 Active
  • Monitor Neural Activity
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  • Human Neuroscience
Blood oxygen level dependent (BOLD) functional MRI is widely used to study human brain function. However, the cellular and molecular mechanisms underlying the BOLD signal remain poorly understood, though many neuroscientists believe the signal reflects contributions from both neurons and astrocytes. Shih and his colleagues will employ cutting-edge tools called Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) to tease out the specific contributions of certain types of astrocytes and neurons to the BOLD signal by selectively activating one group while inactivating the other, and vice versa. The researchers will then repeat their experiments in animal models of chronic neuroinflammation to provide insight into how the BOLD signal is disrupted by diseases involving neuroinflammation.
Circuit and Synaptic Mechanisms of Visual Spatial Attention Haider, Bilal GEORGIA INSTITUTE OF TECHNOLOGY 2018 Active
  • Integrated Approaches

The role of attention in sensory perception is an important question in neuroscience, especially when trying to understand and create better treatments for disorders like schizophrenia, autism spectrum disorders, and attention deficit disorders. Dr. Haider and team will utilize transgenic mice and combine high-density local field potential and neural activity recordings in the visual cortex, patch-clamp recordings from cortical and thalamic synaptic connections, cell-type specific optogenetics, and a well-characterized spatial attention task to elucidate the neural mechanisms of attention at multiple levels: specific cells, synapses, and circuits. 

Circuit Dynamics for encoding and remembering sequence of events Jafarpour, Anna University Of Washington 2019 Active
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  • Human Neuroscience
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Typically, we experience the world as a continuous sequence of events; but when recalling memories, we remember segmented episodes. The hippocampus and prefrontal cortex (PFC) play a role in segmenting, linking, and retrieving memories of associated events, but the neural circuit mechanism of this process is not well understood. Dr. Jafarpour aims to use intracranial encephalography (iEEG) to identify the neural dynamics in the hippocampal-PFC circuit that support the encoding of sequences of words. By combining iEEG with advanced analytical techniques, natural language processing models, and research with patients with hippocampal lesions, this project will offer insights into the neural basis of speech encoding and memory formation. The work may inform the development of neural prosthetics for use by patients with memory impairments.

Circuit mechanisms for encoding naturalistic motion in the mammalian retina Wei, Wei UNIVERSITY OF CHICAGO 2018 Active
  • Integrated Approaches

Understanding how sensory information is extracted by anatomically and functionally defined neural circuits exemplifies one of the many remaining questions surrounding neural circuit function. Using the visual direction-selective circuit in the mouse retina, Dr. Wei and colleagues will perform circuit analyses incorporating a variety of approaches: synapse-specific circuit manipulation, multiphoton calcium imaging, patch clamp electrophysiology, connectomic circuit tracing, and theoretical analysis of information encoding. Results from this work may have broad implications in understanding fundamental principles of neural computation by a well-defined neural circuit.

Circuit mechanisms of evidence accumulation during decision-making Luo, Zhihao Princeton University 2017 Active
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Dr. Luo will use optogenetic tools to inactivate specific brain structures while simultaneously recording neuronal activity across other brain areas in the rat during evidence accumulation tasks. This research could uncover the neural circuits that support the gradual accumulation of evidence during decision making.
Circuit mechanisms underlying learned changes in persistent neural activity Aksay, Emre (contact) Goldman, Mark S Seung, Hyunjune Sebastian Weill Medical Coll Of Cornell Univ 2018 Active
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Understanding how brain circuit-level changes mediate behavioral changes requires detailed knowledge of circuit-wide activity patterns before, during, and after learning. Aksay’s team will study the dynamics of learning by revealing the changes in circuit activity patterns underlying a newly learned behavior. Specifically, they will study the adaptive tuning of the persistent neural activity underlying visual gaze-holding behavior in the zebrafish oculomotor system. The researchers will simultaneously record throughout the oculomotor brainstem and cerebellum during learning, perform anatomical reconstructions at electron microscopic resolution of the imaged circuits, incorporate these data into computational models to make predictions for sites of plasticity, and test those predictions through optical perturbations and electrophysiology. This work could serve as a blueprint for understanding cerebellar involvement in numerous behaviors.
Circuit principles of demotivation in the decision to switch behaviors Crickmore, Michael A Boston Children's Hospital 2019 Active
  • Integrated Approaches

How is a decision made whether or not to switch behaviors? This project aims to use experimental and computational approaches to study how information from competing motivations is processed and integrated to decide whether or not to switch behavior, i.e., to stop one behavior and start another. This work conducted in the Crickmore lab will make use of the Drosophila model to study motivational regulation. The findings will be used to generate circuit and computational models that can provide better insight into motivation.

Circuitry underlying response summation in mouse and primate: Theory and experiment REYNOLDS, JOHN H et al. SALK INSTITUTE FOR BIOLOGICAL STUDIES 2018 Active
  • Integrated Approaches

Each cortical neuron in the brain receives inputs from, potentially, thousands of other cells but produces only one collective response. It is unknown how neurons combine assorted inputs, which often come from many sources -- including sensory stimuli -- into a single response.  Drs. Brunel, Miller, and Reynolds will use visual and experimental optogenetic stimulation to compare responses in the visual cortexes of mice and monkeys as the neurons receive a variety of inputs. The team will also examine how inputs from specific types of neurons influence responses elicited in the cells with which they are communicating.  These findings may increase our understanding of brain circuit function in healthy brains and may provide clues to disorders in which critical circuits are disrupted.

Coarse-graining approaches to networks, learning, and behavior Bialek, William Palmer, Stephanie E (contact) Schwab, David Jason University Of Chicago 2018 Active
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Behavioral neuroscience research produces large quantities of high- dimensional data requiring complicated interrogations. To uncover simpler underpinnings of complex neural recordings, Drs. Palmer, Bialek, and Schwab propose incorporating renormalization group (RG) techniques to a wide range of multi-unit, neural data. The statistical algorithms of their theoretical framework will be freely available and disseminated, as they should be relatively straightforward to apply regardless of discipline. This project could support tractable, efficient analysis of large datasets by enhancing future users’ ability to discern specific properties of neuronal populations critical to behaviors.

Cognitive Restoration: Neuroethics and Disability Rights Fins, Joseph J. Weill Medical Coll Of Cornell Univ 2019 Active
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  • Human Neuroscience
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Many traumatic brain injury (TBI) patients often experience chronic cognitive impairments that disrupt functioning and can interfere with societal reentry – current efforts aim to rapidly restore cognitive function to TBI patients. In doing so, a thorough understanding of the opportunities and challenges posed by rapid cognitive restoration is critical. To address this need, Dr. Joseph Fins and his team will interview patients and family members before implantation of thalamic deep brain stimulation (DBS) devices. These interviews will collect perspectives on risks and benefits, expectations and fears, as well as factors that are weighed during decision making. After implantation, interviews will collect perspectives on the impact of cognitive impairment and restoration. The project aims to develop legal theory that supports social reentry for TBI subjects who have achieved cognitive restoration, paving the way for maximizing patient-centered benefits of any therapeutic advance.

Collaborative Standards for Brain Microscopy Hamilton, Carol M Research Triangle Institute 2018 Active
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Recent tissue-clearing techniques and advances in microscopy have made it possible to produce 3D images of intact brains. to help ensure consistency in data collection and analysis, Dr. Hamilton and her team will develop a set of standards for3D imaging of whole brains for the neuroscience research community.. Dr. Hamilton’s group will convene a Working Group of experts who will work through a consensus process to establish standards that will be distributed to the research community. These standards should help improve the efficiency of imaging research and allow comparisons across studies.

Comprehensive Analysis of a Decision Circuit Pehlevan, Cengiz Samuel, Aravinthan D. Sternberg, Paul Warren (contact) Zhen, Mei California Institute Of Technology 2019 Active
  • Integrated Approaches

Past experiences often drive how an animal develops. How does the brain draw on those experiences to guide developmental choices? Dr. Sternberg’s team will take a detailed look at the C. elegans decision-making circuit during development, using state-of-the-art molecular tools, computational modeling, and functional imaging, to examine how sensory inputs influence the developmental choices an animal makes. With the help of advanced technology, Dr. Sternberg’s colleagues will see how brain circuits change before, during, and after decision making.

Computational and circuit mechanisms for information transmission in the brain Eden, Uri Tzvi Frank, Loren M Ganguli, Surya Kepecs, Adam (contact) Kramer, Mark Alan Machens, Christian Tolosa, Vanessa Cold Spring Harbor Laboratory 2015 Complete
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Dr. Kepecs and colleagues are investigating how information is integrated into decision making, and then further transformed into behavior. This project focuses on understanding information flow across specific regions of the brain in trained rats. By performing parallel, large-scale, simultaneous electrical recordings of neural activity in these different brain regions while the animals perform two different types of decision-making tasks, these researchers hope to observe how activity in one area influences activity in a downstream area. In addition, there are plans to identify and manipulate the activity of neurons that connect these brain areas to understand the causal relationships governing information flow among these regions. Gaining such mechanistic insights into how the brain processes information will provide insights into how both the normal and disordered brain operates.
Computational and circuit mechanisms of decision making Shadlen, Michael Neil Columbia University Health Sciences 2019 Active
  • Integrated Approaches

Many cognitive functions rely on brain mechanisms involved in decision-making. Dr. Shadlen and colleagues aim to better understand how the brain makes increasingly complex decisions by using visual processing as a model. By combining complex behavioral tasks and multichannel neural recordings from multiple brain regions in nonhuman primates, the team will explore context-dependent interactions between brain regions; changes that occur during decision-making; and the timing at which an organism must make two distinct decisions about a single object.

Computational and circuit mechanisms underlying motor control Costa, Rui M. (contact) Jessell, Thomas M. Columbia University Health Sciences 2017 Active
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The mechanisms by which the nervous system produces controlled movements involve interactions between cortical and subcortical regions in the brain, the spinal cord, and muscle, but a clear understanding of these interactions remains elusive. Rui Costa, Thomas Jessell, and colleagues are planning to study the functional and computational logic of connectivity between these motor centers to characterize the role of specific corticospinal neurons during movements. When investigating motor control through cell-type-specific connectivity from brain to spinal cord, the team will use optogenetic manipulations and computational modeling to obtain a clear understanding of these circuit mechanisms. This project – in addition to the use of innovative methods – will also provide an understanding of how these systems are preserved across rodent and nonhuman primate species.
Computational and Circuit Mechanisms Underlying Rapid Learning Buffalo, Elizabeth A University Of Washington 2018 Active
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The circuit mechanisms underlying memory consolidation allow for detailed memory formation. Impairments in these circuits negatively impact patients dramatically with myriad neurological disorders. Dr. Buffalo’s project will study the neural circuits underlying rapid learning, using single-unit and field recordings in human and nonhuman primates (NHP) during the execution of learning- dependent tasks. Alongside electrophysiological recordings in both species during naturalistic and learning task performance and during sleep, the group will perform neural network modeling and state- space analyses. The project could reveal how abstract sensorimotor representations in this circuitry enable “learning to learn” new associations to form memories in humans and NHP.

Connectome 2.0: Developing the next generation human MRI scanner for bridging studies of the micro-, meso- and macro-connectome Basser, Peter J. Huang, Susie Yi Rosen, Bruce R (contact) Wald, Lawrence L Witzel, Thomas Massachusetts General Hospital 2018 Active
  • Human Neuroscience
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Understanding the structural basis of brain function requires spanning multiple spatial scales, from synaptic circuits to whole-brain systems, but current technology is limited in its ability to successfully integrate across these scales. Dr. Bruce Rosen and a team of investigators propose the development of a human magnetic resonance imaging (MRI) scanner that images brain structural connectivity in-vivo. Building upon previous work from the Human Connectome Project (HCP), these tools will advance brain imaging with the capability of estimating cellular and axon level microstructural brain circuits at very high resolution. The project will have the potential to significantly expand our knowledge on hierarchical anatomy and functionality of both healthy and diseased human brains, with impact on both neuroscience research and clinical applications.

Context-dependent processing in sensorimotor cortex Collinger, Jennifer UNIVERSITY OF PITTSBURGH AT PITTSBURGH 2018 Active
  • Human Neuroscience
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When you reach for a beverage, the way you pick up the drink depends on whether it is in a sturdy mug or a delicate champagne flute, as well as your reach configuration. Dr. Collinger and her colleagues plan to investigate the way environmental context affects motor cortex activity as the brain plans movements, such as grasping an object. Two individuals with tetraplegia will receive implants in their motor cortex to record activity while they use brain signals to control a robotic prothesis in a variety of tasks including grasping an object or grasping into empty space, picking up objects of various sizes and materials, and picking up objects for different goals. A better understanding of how the brain prepares these movements may lead to improved devices and therapies for those with sensory or motor problems. 

Cortical circuits and information flow during memory-guided perceptual decisions Sur, Mriganka Massachusetts Institute Of Technology 2014 Complete
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Dr. Sur and his team will combine a number of cutting-edge, large-scale imaging and computational techniques to determine the exact brain circuits involved in generating short term memories that influence decisions.
Cortical dynamics underlying visual working memory Resulaj, Arbora University Of California, San Francisco 2019 Active
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Working memory is crucial to many human functions, and a better understanding of its underlying mechanisms could improve our understanding of memory abnormalities in advanced age. Current hypotheses suggest that working memory is maintained by a hierarchy of interconnected cortical areas, but more work is needed to understand the unique role of each area. Dr. Resulaj aims to study visual working memory at the systems and cellular level in the mouse. Utilizing novel behavior assays, a laser scanning galvo system, and optogenetics, this work ultimately will develop a computational model of visual working memory in the mouse cortex.

Cortical Interactions Underlying Sensory Representations Chen, Jerry BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) 2018 Active
  • Integrated Approaches

Sensory perception involves the transformation of sensory input into mnemonic representations, likely through interactions within and between cortical areas. However, a challenge for neuroscientists has been to distinguish information that is processed locally versus information that is transferred to and from other cortical areas. Using whisker-based paired association tasks in the mouse, Dr. Chen will apply two-photon calcium imaging and optogenetic manipulations to provide insight into these cortical circuits and evaluate predictive models that have been proposed to explain important aspects of perception. Taken together, these efforts could broaden the understanding of sensory representations that undergird perception.

Cortical Signature and Modulation of Pain WANG, FAN et al. DUKE UNIVERSITY 2018 Active
  • Integrated Approaches

There are two components of pain perception: sensory-signal-dependent and affective-cognitive aspects. The primary somatosensory cortex (S1) has been implicated in the affective-cognitive aspect of pain. In certain chronic neuropathic pain conditions, light touch can trigger intense feelings of pain – a hypersensitivity known as mechanical allodynia. Drs. Wang and He will test the hypothesis that S1 neurons that project directly back to the spinal cord facilitate mechanical hypersensitivity, whereas S1 neurons that project intra-cortically to motor cortex suppress this hypersensitivity. The team will use viral-genetic labeling of cortical neurons, in vivo calcium imaging and electrophysiological recordings in mice, optogenetic-assisted slice physiology, trans-synaptic tracing, and computational analyses to study the sensory- and motor-cortical modulation of pain.

Cortical Spatial Processing for Solving the Cocktail Party Problem Han, Xue Sen, Kamal K (contact) Boston University (charles River Campus) 2019 Active
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The cocktail party syndrome describes the process by which the brain tunes into one sound while hearing many others in the background. This often happens when two people have a conversation during a noisy cocktail party. Understanding the neural basis of this cocktail party effect has been a challenge for the auditory research field. To address this, the Sen and Han labs plans to explore how the circuits of the auditory cortex of the mouse brain may play a role in controlling the cocktail party syndrome.  to use novel tools and test hypotheses involving the neural circuits of the auditory cortex, Their results may help researchers understand the circuitry behind a variety of psychological and hearing disorders that disrupt this process.

Cortico-striatal representations of multisensory decision-making Sun, Xiaonan Feinstein Institute For Medical Research 2019 Active
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Activity in the striatum is known to be linked to perceptual decision-making processes orchestrated by the cortex. Dr. Sun proposes to use genetically-encoded calcium indicators to examine cortex-wide activity patterns in mice performing perceptual decision tasks. This will be combined with wide-field calcium imaging in order to correlate behavior with changes in neural activity. The research will enhance our understanding of how activity in the cortico-striatal pathway supports decision-making.

Cracking the Olfactory Code Rinberg, Dmitry New York University School Of Medicine 2019 Active
  • Integrated Approaches

Although olfaction is an important sense used by most animals to interact with their environment, there is a lack of empirical understanding of olfactory processing. Dr. Rinberg and team will collect the first system-wide dataset of neural and perceptual responses to a large, principled set of odorants and leverage recent technical advances in molecular genetics, neural imaging, electrophysiology, opto- and chemo-genetics, human psychophysics, and machine learning to reveal the computational logic of olfaction. The goal of this project is to uncover the rules that determine how various chemical features of an odorant are represented as neural activity, how this neural activity gets transformed as it propagates from the olfactory bulb to the piriform cortex, and the relevance of various features of these olfactory bulb neural responses to eliciting behavior and perception. These experiments will create a community-wide resource with potentially wide-ranging implications for general understanding of sensory information neural processes.

Crowd coding in the brain:3D imaging and control of collective neuronal dynamics Kanold, Patrick O (contact) Losert, Wolfgang Plenz, Dietmar Univ Of Maryland, College Park 2014 Complete
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Dr. Kanold and his team propose cutting edge methods to stimulate neurons at different depths in the auditory cortex, and will use new computational methods to understand complex interactions between neurons in mice while testing their ability to hear different sounds.
DANDI: Distributed Archives for Neurophysiology Data Integration Ghosh, Satrajit Sujit (contact) Halchenko, Yaroslav O Massachusetts Institute Of Technology 2019 Active
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Dr. Ghosh and colleagues propose to develop a new computer infrastructure for scientists to share, collaborate, and process neurophysiological data. The data will be open to both scientists and also be used to engage high school and college students. The team will also develop tools to facilitate data submission and access and to encourage adoption of the Neurodata Without Borders data standard.

Data Archive for the Brain Initiative (DABI) Duncan, Dominique Pouratian, Nader Toga, Arthur W (contact) University Of Southern California 2018 Active
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This project develops DABI (Data Archive for the Brain Initiative) to aid the dissemination of human neurophysiological data generated through the BRAIN Initiative. Incorporating infrastructure from a pre- existing hub for delivering effective informatics and analytics solutions for major projects in the study of neurological diseases, Drs. Toga, Duncan, and Pouratian will aggregate data related to human electrophysiology, making the data broadly available and accessible to the research community. The group plans to incorporate analysis tools with user interfaces, implement tools for data management and use, and link metadata across different data modalities. The overarching goal of this project is to secure, link, and disseminate BRAIN Initiative data with all pertinent recording and imaging parameters coming from participating sites

Data interface and apps for systems neurophysiology and imaging Van Hooser, Stephen D Brandeis University 2018 Active
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Many labs develop unique software to manage and interpret their findings, but those programs are often specific for certain types of datasets, making them difficult to share among researchers. Dr. Van Hooser’s team plans to create an interface standard that establishes a common set of processes for accessing neurophysiological and imaging data. The standard will be tested, and revised accordingly, based on feedback from graduate students and postdoctoral researchers during data access events, or “hack-a-thons.” The interface standard will help increase the speed of research and make data widely available, allowing individuals outside of the neuroscience and research communities to make discoveries.

Data-driven analysis for neuronal dynamic modeling Mishne, Gal Yale University 2018 Active
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The communications and interactions between neurons across the sensory-motor system require additional investigations with novel methodologies to understand dynamic activity patterns underlying behavior. Dr. Mishne will develop modular mathematical tools to automatically analyze massive amounts of high-resolution, spatiotemporal, neuronal activity data gathered from mice performing a reaching task. The proposed calcium imaging data will be processed in three modules that: develop methods for ROI (region of interest) extraction, use tensors and non-linear tools for multi-modal integration of neuronal activity with behavior, and predict future behavioral responses using a recurrent neural network approach. These methods for automated analysis, organization, and modeling of calcium imaging data gathered during behavioral tasks will be available for use by the entire community.

Decoding the neural basis of resting-state functional connectivity mapping Hillman, Elizabeth M Columbia University Health Sciences 2017 Active
  • Monitor Neural Activity
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  • Human Neuroscience
Resting-state functional magnetic resonance imaging (rs-fMRI) detects how brain regions are synchronized, forming networks that support normal function. Understanding these networks may help diagnose and treat disease. Elizabeth Hillman’s team will use novel optical imaging, capturing neural activity and blood flow dynamics, to characterize cellular dependencies, pathways, behavioral correlates, and blood flow interactions of resting-state spontaneous neural activity. Data will be acquired using novel measurement and circuit manipulation techniques in awake, behaving mice, and rs-fMRI analysis of equivalent human neurovascular activity. The aggregate data will yield predictive models of network activity and the relationships between resting-state activity in specific cell types and blood flow dynamics. By optimizing and validating rs-fMRI analysis, this project could transform rs-fMRI into a reliable technique for studying the brain in health and disease.
Defining Cell Type Specific Contributions to fMRI Signals Lee, Jin Hyung Stanford University 2017 Active
  • Monitor Neural Activity
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  • Human Neuroscience
Functional magnetic resonance imaging (fMRI) allows non-invasive study of human brain function. However, how specific cell types contribute to fMRI signals remains elusive, complicating fMRI interpretation. Jin Hyung Lee’s team will measure cell-type-specific, whole-brain network function using fMRI while using optogenetics to selectively stimulate distinct neural circuit pathways in the basal ganglia. These pathways are involved in action planning and reward, and are implicated in disorders as diverse as Parkinson’s disease, depression, and substance use disorders. Optical imaging will confirm fMRI signal sources with cell-type specificity. The group will computationally model these interaction dynamics to demonstrate how this unique approach can be used to uncover whole-brain circuit functions. This project could enable researchers to systematically design therapies to restore normal circuit function in disorders like Parkinson’s disease.
Defining Neuronal Circuits and Cellular Processes Underlying Resting fMRI Signals Milham, Michael Peter Schroeder, Charles E (contact) Nathan S. Kline Institute For Psych Res 2016 Active
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  • Human Neuroscience
Methods for measuring intrinsic functional connectivity (iFC), a measure of correlation between spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, can be used to quickly map in high detail the functional architecture of the human brain. However, the neural circuits underlying the BOLD-iFC relationship remain poorly specified. Schroeder and his colleagues propose to use a variety of measurement tools in humans and monkeys to investigate this relationship. The researchers will then employ established modeling and computational methods to help construct a comprehensive model that connects large-scale iFC to underlying microscale activity at the neural circuit level. The findings from this project may be used to improve the efficiency of iFC measurements, which could have widespread clinical implications, particularly in the discovery of biomarkers for various brain disorders.
Defining the anatomical, molecular and functional logic of internal copy circuits involved in dexterous forelimb behaviors Azim, Eiman Salk Institute For Biological Studies 2019 Active
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Skilled control of forelimbs is one of the most important roles of the mammalian motor system and requires a circuitry in the nervous system that allow for rapid adjustments. Using molecular, anatomical, and behavioral tools, this project aims to study how a component of that circuitry, the propriospinal neurons in the spinal cord, relays information to and from the brain.

DELINEATING CELL-SPECIFIC OUTPUT PATHWAYS OF THE GPe THAT SUPPORT LONG-LASTING BEHAVIORAL RECOVERY IN DOPAMINE DEPLETED MICE Gittis, Aryn Hilary Carnegie-mellon University 2018 Active
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Deep brain stimulation in the basal ganglia system, a treatment for Parkinson’s disease, provides only transient relief of motor symptoms. Gittis and colleagues will identify which neuronal subpopulations in the external globus pallidus (GPe) within the basal ganglia are required to induce long-lasting motor rescue in dopamine-depleted mice. Optogenetics and in vivo recordings will be used to assess the impact of modulating specific neuronal subpopulations on GPe circuit dynamics and on behavior. Virally-targeted circuit mapping will elucidate the pathways through which GPe neuronal subpopulations mediate their motor effects. If successful, this work will advance the current understanding of basal ganglia circuitry, and potentially lead to better treatments for motor dysfunction.
Dendritic Computation and Representation of Head Direction in Retrosplenial Cortex Harnett, Mark Thomas Massachusetts Institute Of Technology 2019 Active
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How do individual neurons in the mammalian cortex integrate multiple streams of input to guide behavior? In this project scientists will image the dendrites and cell bodies of neurons to determine how head direction and visual information is combined by neurons in a region of the brain called the retrosplenial cortex during navigational behaviors. This research will enhance our understanding of associative cortical function and provide new insights into cellular- and circuit-level mechanisms of navigation.

Determination of olfactory bulb cell identity through the integration of single cell epigenomic and transcriptomic data Doyle, Wayne University Of California, San Diego 2019 Active
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Olfaction is an extremely important sensory modality across species, and it is one of the first to be disrupted in many neurodegenerative diseases. Dr. Doyle will conduct a full census of all cell types in the mouse olfactory bulb, to better understand information integration and processing in the olfactory system. This approach will utilize transcriptomic (single cell RNA-sequencing) and epigenomic (single nucleus methylome- and single nucleus ATAC-sequencing) data generated by members of the BRAIN Initiative Cell Census Network (BICCN). Overall, this will allow for a fuller understanding of the roles of cell diversity, regulatory elements, and transcription factors in the mouse olfactory system.

Determining the role of muscle afferent signals in cortical proprioceptive representation Blum, Kyle Northwestern University At Chicago 2019 Active
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While it is known that proprioception plays an important role in movement, how the brain translates proprioceptive information into information for movement in the somatosensory cortex (S1) is poorly understood. Dr. Blum aims to study how active and passive movements of limbs elicit different responses from muscle spindles and Golgi tendon organs, especially as reflected in area 3a of S1. Using electrophysiological data, arm kinematic measurements, and EMGs in monkeys trained to perform an arm-reaching task, this research aims to model afferent proprioceptive signals and motor outputs in a neural network model. These results will improve our understand of the neural control of movement.

Developing novel chemo-optogenetic tools for in vivo applications Lam, Pui Ying University Of Utah 2019 Active
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Optogenetics and chemo-optogenetics are emerging tools for neuroscience research, providing ways to modulate cell function with light. However, current limitations for these tools include limited ability to target cells deep in the brain, the relatively small effects they elicit, and safety concerns over long-term use. Dr. Lam proposes to develop new chemo-optogenetic tools to address these issues, based on the TRPA1 and TRPV1 receptor channels. Further, she will develop this technology for in vivo use, testing its utility in behavioral assays of zebrafish. The work will improve our ability to understand brain circuit function, and will create a platform for the discovery of other novel chemo-optogenetic approaches that mimic natural cell activity.

Development and validation of empirical models of the neuronal population activity underlying non-invasive human brain measurements Devinsky, Orrin Dijkhuizen, Rick M Petridou, Natalia (contact) Ramsey, Nicolas Franciscus Winawer, Jonathan A University Medical Center Utrecht 2016 Active
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  • Human Neuroscience
A major obstacle in the study of human brain function is that we currently have a limited understanding of how the measurements made by different instruments, such as fMRI and EEG, relate to one another and to the underlying neuronal circuitry. To overcome this challenge, Petridou and her colleagues will combine a number of invasive (optical imaging, ECoG) and non-invasive (functional MRI, MEG and EEG) hemodynamic and electrophysiological measurements in humans and rats. By obtaining recordings from these multiple techniques, the researchers will be able to unequivocally link electrophysiological and fMRI signals. Reconciling these different signals will lead to breakthroughs in understanding the dynamic activity of the human brain and the improvement of disease models of the nervous system.
Development of 7-T MR-compatible TOF-DOI PET Detector and System Technology for the Human Dynamic Neurochemical Connectome Scanner Catana, Ciprian MASSACHUSETTS GENERAL HOSPITAL 2018 Active
  • Human Neuroscience
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Systems capable of simultaneous positron emission tomography (PET) and magnetic resonance imaging (MRI) are now available, but PET technology in these systems lacks the capability of tracking dynamic changes at high spatio-temporal resolution. Dr. Ciprian Catana and a team of investigators plan to develop a PET detector that can be successfully integrated with a 7-Tesla MRI scanner with high sensitivity and resolution. After designing and evaluating a scalable PET detector module, the group will investigate and address hardware challenges of developing high performance MR-compatible PET technology. The successful development of this novel PET technology will enable imaging of the human brain’s dynamic neurochemical connectome and significantly advance our understanding of human brain function, neurochemistry, and physiology.

 

Development of Line-Scan Temporal Focusing for fast structural imaging of synapse assembly/disassembly in vivo Boivin, Josiah R Massachusetts Institute Of Technology 2017 Active
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Dr. Boivin will contribute to the development of high-resolution, high-throughput Temporal Focusing (TF) two-photon microscopy to achieve real-time monitoring of synapse assembly/disassembly in developing neural circuits in vivo in the mouse brain.
Development of predictive coding networks for spatial navigation Dragoi, George Yale University 2018 Active
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Sequential neuronal attractors (i.e., neural network patterns with stable functional dynamics) have mainly been studied in adult animals, which accumulate spatial experience during development. Therefore, the early-life development of sequential neuronal attractors for encoding future navigation experiences (i.e., predictive coding) has remained mysterious. George Dragoi and colleagues seek to elucidate the roles of innate versus experiential factors in the emergence of internally-generated (hippocampus-mediated) representations of the world. While controlling prior spatial experience, they will record chronically from hippocampal neuron ensembles in developing, freely-behaving and sleeping rats, and will identify and analyze predictive coding network properties. This project could aid the study of neuronal ensemble pattern disruptions, with implications for disorders with developmental etiologies like schizophrenia and autism.
Dexterous BMIs for tetraplegic humans utilizing somatosensory cortex stimulation Andersen, Richard A California Institute Of Technology 2016 Active
  • Human Neuroscience
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As of 2016, approximately 160,000 Americans are living with partial or complete tetraplegia, a severe form of paralysis in which patients lose partial or total function and sensation in all four limbs. Many of these patients have sufficiently intact brain circuits to plan movements, but are unable to act on those plans due to paralysis at the spinal level. In this project, Andersen and his team will work with tetraplegic patients implanted with a brain machine interface (BMI) to record from and stimulate brain circuits. Their goal is to understand how the brain encodes the ability to reach for and grasp an object. They also propose to stimulate somatosensory cortex to restore sensory cues the hands would normally receive when grasping an object, and to combine these recording and stimulating efforts to design bi-directional BMIs. This work could lead to improved quality of life for patients with tetraplegia, and could inform treatment of motor impairments due to other causes including stroke and neurodegenerative diseases.
Diagnosis of Alzheimer's Disease Using Dynamic High-Order Brain Networks Shen, Dinggang (contact) Yap, Pew-thian Univ Of North Carolina Chapel Hill 2016 Active
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Despite being the most common form of dementia, Alzheimer’s disease (AD) has no known cure and current clinical diagnosis relies on subjective neuropsychological and neurobehavioral assessments. Shen and his team plan to create machine learning-based algorithms that will hone in on changes to the functional connectivity of brain networks over time—as measured by neuroimaging techniques such as diffusion MRI—as possible indicators of mild cognitive impairment (MCI), which generally occurs well before AD symptoms. The researchers will design their diagnostic tools with the flexibility to also improve the success of the early detection of other neurological disorders, including schizophrenia, autism, and multiple sclerosis.
Discovering dynamic computations from large-scale neural activity recordings Engel, Tatiana Cold Spring Harbor Laboratory 2018 Active
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Dynamic neuronal activity patterns underlie behavioral and cognitive functions in healthy and disordered brains, but large-scale recordings of this activity produce massive amounts of data requiring complex computations. Dr. Engel’s project provides a novel theoretical framework for analytically modeling the process by which temporally diverse responses of single neurons contribute to population activity during decision making. The group will validate unbiased, computational methods to examine dynamic activity in primate and mouse cortices and incorporate this framework into their freely available “BrainFlow” software and visualization tools.

Dissecting circuits for local and long-range competitive inhibition in the mouse superior colliculus Mysore, Shreesh P Johns Hopkins University 2019 Active
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The superior colliculus is an area found deep inside the brain that guides the brain’s reaction to competing stimuli and is involved in spatial attention control. In this project, the Myshore group will examine the role local and long-range inhibitory neural circuits play in controlling these behaviors. Initial experiments will be performed on mice shown visual stimuli. The researchers will use optogenetics to manipulate inhibitory neurons and endoscopic calcium imaging to record any resulting changes in excitatory neuronal activity. The results may help researchers better understand the role inhibitory circuits play in behavior and brain diseases.

Dissecting distributed representations by advanced population activity analysis methods and modeling Druckmann, Shaul Stanford University 2019 Active
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Sensory information passes through multiple brain areas to ultimately lead to behavior, but there is no clear understanding of how these multiple brain areas interact. Dr. Shaul Druckmann and team will develop analytical techniques that will facilitate interpreting the interactions among brain areas by recording brain activity and studying strategic perturbations of the data patterns. Working with experimental collaborators, they will use three high-quality datasets to design analytical approaches to interpret this data. They will first develop statistical metrics, then validate dimensionality reduction approaches that capture complex data in more interpretable forms. Finally, they will adapt modeling approaches to create mechanistic models of how circuit structure supports the activity dynamics of sensory information. These approaches and tools will have the potential to reveal how brain areas interface with each other and how these interactions shape behavior.

Dissecting the dual role of dopamine in context-dependent and learned behaviors Ruta, Vanessa Rockefeller University 2019 Active
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Dysfunctions in dopamine signaling underlie a number of neuropsychiatric conditions; however, the diversity of roles dopamine plays in the brain has made it difficult to study. Using Drosophila as a model, Dr. Ruta and colleagues propose to use cutting-edge techniques to study how reward and locomotor signals are translated to different patterns of dopamine release and how they engage distinct dopamine receptor signaling cascades. Specifically, the team will study the fly’s mushroom body, which is involved in olfactory processing, learning, memory, and reward. This region is especially amenable to these experiments due to its relatively simple structure and available genetic tools. The results may shed light on the role of dopamine signaling in modulating behavior.

Dynamic network computations for foraging in an uncertain environment Angelaki, Dora (contact) Dragoi, Valentin Pitkow, Zachary Samuel Schrater, Paul R Baylor College Of Medicine 2015 Complete
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The computational strategies and underlying mechanisms the brain uses to enable animals to interact flexibly with their environment are poorly understood. These researchers will use large-scale, wireless, electrical recordings from six relevant, interconnected brain regions in freely-behaving monkeys to record neuronal activity while the animals engage in foraging behavior-a natural task that involves sensory integration, spatial navigation, memory, and complex decision-making. The research team will use theoretical models of decision-making to interpret the neural activity data gathered as the animals interact with their environment, with the ambitious goal of understanding how brains create and use internal models of the world.
Dynamic Neural Mechanisms of Audiovisual Speech Perception Beauchamp, Michael S (contact) Schroeder, Charles E Baylor College Of Medicine 2019 Active
  • Human Neuroscience
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  • Monitor Neural Activity

Speech perception often lies at the heart of our interactions with other people. By nature, it is multisensory, combining auditory information from the voice with visual information from the face. However, there is a large gap in our knowledge about this critical cognitive skill because most experimental techniques available in humans have poor spatiotemporal resolution. In this strategic opportunity to study patients undergoing clinically-indicated brain surgery, Dr. Michael Beauchamp and his team will use intracranial recording (iEEG) in humans to study the neural mechanisms of speech perception. In addition to high-resolution intracranial electrode grids, the group will also leverage non-penetrating electrodes that are safely placed on the cortical surface of the brain. This multi-pronged approach will enable the group to study the organization and operation of the brain during audiovisual speech perception, providing a better understanding of this important human skill.

Dynamic Neural Mechanisms of Audiovisual Speech Perception Schroeder, Charles E Columbia University Health Sciences 2016 Active
  • Human Neuroscience
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Limitations in spatial and temporal resolution with current non-invasive brain imaging technologies prevent a thorough understanding of the mechanisms of speech perception – from audio-visual (AV) integration, to encoding, and cognitive interpretation. Dr. Charles Schroeder proposes directly recording from neurons in epilepsy patients while they process AV speech using electrocorticographic (ECoG) techniques to determine how oscillations in neuronal excitability influence processing and encoding. Not only could this project improve our ability to treat neurological disorders affecting speech and language processing, but it may allow a more comprehensive investigation into the functional interactions between brain circuits and perception.
Dynamics and Causal Functions of Large-Scale Cortical and Subcortical Networks SCHALK, GERWIN WADSWORTH CENTER 2018 Active
  • Human Neuroscience
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To produce a behavior, brain areas need to talk to each other. This communication has been difficult to study in humans, but novel tools provide a window into these conversations. Dr. Schalk and his colleagues plan to establish a consortium that will bring together a large cohort of study subjects and experts across scientific disciplines. They will record from state-of-the-art brain implants to investigate which regions are involved in speech, language, and music awareness; to measure how stimulating certain areas affects speech and language; and to explore how areas talk to one another during changing speech perception. These results should increase understanding of how brain regions interact, which may provide insights to treating neurological and psychiatric disorders.

EFFECTIVE CONNECTIVITY IN BRAIN NETWORKS: Discovering Latent Structure, Network Complexity and Recurrence. Hanson, Stephen Jose Rutgers The State Univ Of Nj Newark 2016 Active
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A longstanding goal of neuroscience has been matching specific functions to local brain structure and neural activity. Despite success in identifying brain areas associated with cognitive tasks such as memory, attention, and language, many areas engaged during cognitive tasks are often considered “secondary” and are consequently ignored. One weakness in current methods to associate brain regions with specific functions has been the reliance on direct correlation between increased neural activity and task performance. To identify and assess how secondary areas contribute to important cognitive tasks, Hanson and his colleagues plan to extend IMaGES and develop new functional brain imaging analysis software to search for brain areas with less intuitive, but still relevant, connections to certain tasks. This project will advance efforts to analyze information flow in the brain and determine how neural pathways are altered in both health and disease.
Effects of standard fMRI calibrations on the diverse microvascular blood flow and oxygenation responses in cortical layers Sencan, Ikbal Massachusetts General Hospital 2019 Active
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Various improvements are being considered to create next generation biophysical models of blood oxygenation and fMRI measurements in brain. Dr. Sencan plans to quantify spatial and temporal diversity in cortical metabolism in order to inform these scientific advancements. By measuring processes of cortical oxygenation, metabolic rate, and blood flow responses at microvascular scales, she aims to understand how these processes contribute to brain function and vary across age, region, and depth in the awake, mouse brain. To achieve these goals, she will use novel experimental techniques, related to faster, deeper, and more realistic imaging of oxygen concentration. This work may support better interpretation of clinical results derived through imaging technologies like fMRI.

Efficient resource allocation and information retention in working memory circuits Ching, Shinung (contact) Snyder, Lawrence H Washington University 2019 Active
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Working memory - our ability to temporarily hold information in mind - is important for many aspects of normal human cognition, but there are critical gaps in our knowledge of how the brain remembers and stores multiple items. Through a combination of behavioral tests and computational modeling, Dr. ShiNung Ching and his team will test the validity of their theory that the organization of networks optimizes efficient resource allocation. Key to this project is the integration of experimental and computation methods to tightly link observed behavioral phenomena, theory, and underlying neural mechanisms. Because dysfunction of working memory occurs in numerous neuropsychiatric illnesses, the success of this project could inform improvements in diagnosing and treating these disorders.

ELECTROPHYSIOLOGICAL SOURCE IMAGING GUIDED TRANSCRANIAL FOCUSED ULTRASOUND HE, BIN Carnegie-mellon University 2017 Active
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Noninvasive neuromodulation technologies use a variety of electrical, magnetic, optical, and sonic techniques to stimulate the brain. The ensuing modulation of brain network dynamics can be used as a tool to study healthy brain processes, as well as for treatment of brain disorders. He’s team will develop an acousto-modulated electrophysiological source imaging (ESI) technique with improved spatial precision, and use it to monitor and image transcranial focused ultrasound (tFUS)-induced brain activity in real-time. The group will validate this integrated ESI-guided tFUS system in rats, using simultaneous intracranial recordings of neural spikes and local field potentials, and ultimately test it in human subjects. This non-invasive neuromodulation, with high spatiotemporal precision, promises stimulation which is individualized and responsive to dynamic neural activity.

Elementary Neuronal Ensembles to Whole Brain Networks: Ultrahigh Resolution Imaging of Function and Connectivity in Humans Ugurbil, Kamil University Of Minnesota 2017 Active
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  • Human Neuroscience
Obtaining a comprehensive view of the human brain – from neuronal circuitry up to whole-brain functional and structural connectivity – requires advances in current magnetic resonance imaging (MRI) methods that span spatial and temporal scales. Kamil Ugurbil and a team of multi-institution researchers are improving on the technologies required to generate a previously unavailable, 10.5 Tesla, high-quality MR image. Ugurbil aims to develop methods that exploit the signal-to-noise ratios available at ultrahigh fields, improve image reconstruction, and use these technological developments to create a publicly available dataset for novel computational modeling. These developments will permit investigation of brain function and connectivity in order to reach and span currently unavailable spatial scales, going from neuronal ensembles composed of few thousand neurons to the entire human brain networks, enabling the integration of animal and human studies.
Elucidating the Wiring and Rewiring of Poly-synaptic Memory Circuits by Directed Stepwise Trans-neuronal Tracing Xu, Wei Ut Southwestern Medical Center 2018 Active
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Elucidating the organization of long-range poly-synaptic neuronal pathways is essential to understanding brain functions and the pathogenesis of brain disorders. Xu’s team will develop and utilize technologies to observe hypothesized circuit rewiring during learning and memory. Modified viral vectors will enable controlled, stepwise trans-neuronal tracing, which will be used to define distinct neuronal subpopulations in the hippocampus based on their poly-synaptic inputs/outputs. The team will then manipulate specific subpopulations to determine if different neuronal groups convey distinctly sensory information and, in turn, adjust different aspects of behavior. Lastly, the connectivity of neurons of interest will be traced—before and after a learning process—to examine if learning and memory alters connectivity. This work could deepen our understanding of the neurobiology of memory in health and disease.
Embedded Ensemble Encoding Antic, Srdjan D Lytton, William W (contact) Suny Downstate Medical Center 2016 Active
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The enormous complexity of brain interactions provides numerous challenges in understanding and treating brain diseases such as autism, schizophrenia, and Alzheimer’s disease. A large part of this complexity lies in “the neural code,” which describes how cells in the brain communicate with one another. Lytton and his colleagues propose the development of a novel embedded-ensemble encoding theory for understanding the creation of ensembles of neurons that are believed to generate thoughts, perceptions, and actions. The heart of this theory states that temporary neuronal ensembles form among groups of neurons across the brain whose activity becomes synchronized. The ultimate goal of this project is to bridge the gap between single neurons and neural networks and derive fundamental insights into cortical function that may advance the understanding of a variety of neurological diseases.
Emergent dynamics from network connectivity: a minimal model Curto, Carina Pennsylvania State University-univ Park 2016 Active
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Many networks in the brain exhibit emergent dynamics: that is, they display patterns of neural activity that are shaped by the intrinsic structure of the network, rather than modified by an external input. Such dynamics are believed to underlie central pattern generators for locomotion, oscillatory activity in cortex and hippocampus, and the complex interplay between sensory-driven responses and ongoing spontaneous activity. The goal of this research by Curto and her colleague is to develop a theory of how emergent dynamics can arise solely from the structure of connectivity between neurons. Having a deeper understanding of the dynamics of neural circuits is critical for studying diseases in which those dynamics are thought to be disrupted, such as Parkinson's disease, schizophrenia, and epilepsy.
Enabling ethical participation in innovative neuroscience on mental illness and addiction: towards a new screening tool enhancing informed consent for transformative research on the human brain Roberts, Laura W Stanford University 2017 Active
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The NIH BRAIN Initiative aims to accelerate the development of innovative neurotechnologies and their application to reduce the burden of brain disorders, including mental illnesses and substance use disorders. However, because the brain is central to our humanity, this kind of research raises profound neuroethics issues, including questions about personal identity, and socially acceptable limits on novel neurotechnologies. Further, research involving participants with brain disorders is complex because these disorders can affect cognition, emotion, behavior, and decision-making capacity. In this project, Dr. Roberts and colleagues will assess the neuroethics issues encountered in neuroscience research related to mental illness and addiction through interviews with neuroscientists, neuroethicists, and institutional review board members. They will also study factors that influence research decision-making by people with mental illness and addiction, as compared with healthy controls and people with diabetes. Finally, they will develop a screening tool to enhance informed consent, as an evidence-informed practice to facilitate ethically sound cutting-edge human neuroscience research.
Enabling Multi-Tracer SPECT Studies of the Human Brain Peterson, Todd VANDERBILT UNIVERSITY MEDICAL CENTER 2018 Active
  • Human Neuroscience
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A comprehensive view of the brain requires quantifying multiple properties of the brain simultaneously. However, obtaining those measures with comparable levels of sensitivity and resolution remains challenging. Single-photon emission computed tomography (SPECT) utilizes multiple radiotracers that emit gamma rays at specific energies, making simultaneous measurement of multiple molecular imaging probes possible. Dr. Todd Peterson and a team of investigators will develop SPECT radiation detector technology that improves energy resolution over traditional detectors, thereby minimizing crosstalk and separating the signal that previously limited the quantitative accuracy of multi-tracer imaging studies. By aiming to improve multi-tracer SPECT technology, the researchers will deliver an imaging approach that will pave the way for simultaneous, quantitative multi-tracer imaging studies of the human brain.

 

Engineering optogenetic tools for studying neuropeptide activity French, Alexander Robert Purdue University 2017 Active
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Dr. French will develop a high throughput screening platform to identify peptides that activate opioid receptors in response to light, creating high-resolution tools to study the function of specific opioid neural circuits in the brain.
Ensemble neural dynamics in the medial prefrontal cortex underlying cognitive flexibility and reinforcement learning Ganguli, Surya Schnitzer, Mark J (contact) Stanford University 2017 Active
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The prefrontal cortex plays a critical role in cognitive flexibility and decision-making, but the neural circuits underlying these processes remain unclear. Mark Schnitzer and Surya Ganguli are applying reinforcement learning theory (i.e., how to select optimal future actions based on past actions) to understand how neural ensembles in prefrontal cortex guide behavior. With an innovative mini-microscope for neural calcium imaging in active mice, the team plans to use this method to acquire stable, long-term recordings of neural ensemble dynamics, then create a neural network model that tests how these dynamics affect an animal’s actions. A clear understanding of this important neural circuit has the potential to inform clinical applications for psychiatric conditions for which cognitive flexibility is compromised.
Ethical Safeguards for Exit and Withdrawal from Implanted Neurotechnology Research Sankary, Lauren Cleveland Clinic Lerner Com-cwru 2017 Active
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Dr. Sankary will combine an assessment of the experience of research participants exiting from research studies involving implanted neurological devices with a critical evaluation of existing research practices and regulations that protect these subjects. The goal of this research is to determine the responsiveness of these safeguards to patient concerns and lay the groundwork for development of evidence-based guidelines for the ethical conduct of this research.
Ethics of Patients and Care Partners Perspectives on Personality Change in Parkinsons disease and Deep Brain Stimulation Kubu, Cynthia M. S. Cleveland Clinic Lerner Com-cwru 2017 Active
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The nature and extent of personality changes following deep brain stimulation (DBS) for the treatment of Parkinson's disease (PD) are unclear. Dr. Kubu and colleagues will analyze patients’ and caregivers’ perspectives on personality characteristics (e.g., extroversion, humility) at different stages of PD and over the course of DBS (patients within one year of diagnosis, within 5 -7 years of diagnosis, and those undergoing DBS). This study will shed light on participant's most valued personality characteristics, and whether those characteristics are captured in the existing informed consent process; the influence of PD and/or DBS on personality; and the extent of agreement between patients’ and caregivers’ perceptions of personality change. These data will facilitate an enhanced, iterative informed consent process that includes systematic assessment of patients’ perceived personality changes, values, and goals; will inform understanding of identity and autonomy in the context of DBS; and may allow clinicians to ease the fears of patients receiving DBS.
Expanding access to open-source data acquisition software for next-generation silicon probes Siegle, Joshua H Allen Institute 2019 Active
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Determining how brain cells communicate with each other bolsters understanding of the causes of disorders. The new Neuropixels probe allows for highly detailed recordings of neurons communicating; however, sophisticated software is required to use this tool and to understand the data it generates, which include nearly 1000 recording sites from a single probe. For other labs to use this system, a support network is needed to address user requests, maintain the software code, and improve documentation. Through this project, Dr. Siegle and colleagues will support other labs that wish to use Neuropixel probes to better understand the underpinnings of neurological and mental disorders.

Filtered Point Process Inference Framework for Modeling Neural Data Brown, Emery N. Massachusetts General Hospital 2016 Active
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Spikes are key elements of neural computation and methods to improve the extraction of spike data from calcium imaging and other similar imaging methods are much in demand. Existing techniques are either extremely slow or susceptible to noise. Brown and his colleagues plan to develop a mathematical framework for analyzing neuronal spikes, and to apply it to the analysis of calcium imaging data in behaving mice and to neuroendocrine data related to the secretion of hormones in humans. This framework will shed light on sensory encoding in the rodent brain. It will also aid our understanding of pathological neuroendocrine states and improve the efficacy of treatments of hormonal disorders, including diabetes, obesity and osteoporosis.
Foundations of MRI Corticography for mesoscale organization and neuronal circuitry Feinberg, David Alan University Of California Berkeley 2016 Active
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  • Human Neuroscience
While functional MRI (fMRI) with low spatial resolution is useful for capturing a picture of dynamic activity across the entire brain, performing fMRI at high-resolution may accurately distinguish neuronal activity in cortical layers and columns. Feinberg and his colleagues plan to use recently developed high-resolution fMRI techniques with a number of other techniques, including optogenetics, transcranial magnetic stimulation, and electrocorticography, to identify and stimulate the various aspects of neural activity that drive the fMRI signal. These measurements will enable bridging neuronal activity to the level of cortical layers and columns identifiable in high-resolution fMRI signals to help better understand the underlying biology of non-invasive imaging of brain circuitry.
From ion channel dynamics to human EEG and MEG: multiscale neuronal models validated by human data Bazhenov, Maksim V (contact) Cash, Sydney S Halgren, Eric University Of California, San Diego 2018 Active
  • Human Neuroscience
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Non-invasive imaging methods, such as electroencephalography (EEG) and magnetoencephalography (MEG), are commonly used in basic research studies and in some diagnostic procedures. These methods derive neural signals by summating over the activity of millions of neurons, but the dynamics of the underlying cellular signal and circuit function remain elusive. Drs. Bazhenov, Cash, and Halgren, along with a team of investigators, will use biophysical and neural modeling to predict the cellular dynamics underlying EEG and MEG signals, which they will then confirm using extensive intracranial recording data. This bidirectional approach that generates predictions – which can then be validated with data – has the potential to identify a crucial link between neuronal and synaptic responses that subsequently give rise to macroscopic EEG and MEG recordings.

From microscale structure to population coding of normal and learned behavior Debello, Wiliam Mcintyre Ellisman, Mark H Fischer, Brian J Pena, Jose L (contact) Albert Einstein College Of Medicine 2017 Active
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The mechanisms underlying how neuron populations execute auditory-driven animal behavior (i.e., sound localization), and how experience sculpts the behavior and the underlying neural representation of auditory space, are currently unknown. To better understand the relationship between activity patterns across neural populations and behavior, Jose Pena and colleagues will study the sound-driven, head-orienting responses of barn owls. The team will combine electrophysiological, anatomical, and behavioral analyses to map neuronal population activities upon presentation of sounds. They will investigate the network architecture supporting the activity patterns, as well as how the network changes with learning. The main goal of this project is to envision a complete understanding of auditory localization, from the microcircuit to population coding to behavior.
Functional Architecture of Speech Motor Cortex Chang, Edward University Of California, San Francisco 2016 Active
  • Human Neuroscience
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Speaking is one example of a complex behavior that most humans can perform effortlessly, but scientists do not fully understand how the brain is able to drive speech production. Building on their prior work on the neural representation of articulatory and acoustic feature representations of speech, Chang and his team will conduct ultra high-density electrocorticography in epilepsy patients to study how the ventral sensorimotor cortex encodes the movements that produce speech, and how the prefrontal cortex is able to exert inhibitory control over speech. This work will advance our understanding of communication disorders, and refine the ability of clinicians to map speech areas of the brain in their patients.
Functional Dissection of Neural Circuitry Underlying Parenting Behavior Hong, Weizhe University Of California Los Angeles 2019 Active
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It remains unclear what accounts for differences in parenting behavior in different sexes and physiological states. Parenting behaviors in mice have been found to be governed in part by GABAergic neurons within the medial amygdala. This project will take advantage of cutting-edge functional manipulation and imaging techniques to determine the neural mechanisms and circuitry underlying these differences in parenting behaviors.

Functional dissection of thalamocortical interactions through genetically-defined TRN subnetworks Feng, Guoping (contact) Halassa, Michael M Massachusetts Institute Of Technology 2019 Active
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The thalamic reticular nucleus (TRN) is a part of the brain that is important for many activities such as sensory processing, arousal, and cognition. Disrupted TRN function could underlie behavioral deficits seen in disorders such as schizophrenia, autism, and ADHD. However, little is understood about how the circuitry in the TRN contributes to these functions. Using molecular tools, anatomical tracing, and in vivo recordings, the team for this project will study how organization of the TRN circuitry gives rise to function, specifically how distinct subgroups of TRN neurons form subnetworks that contribute to different aspects of sensory processing, arousal, and cognition.

Functional implications of a patch/matrix-like compartmental organization in the mouse inferior colliculus Lesicko, Alexandria Marie University Of Pennsylvania 2019 Active
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The brain’s inferior colliculus is described to have a patch- or matrix-like “modular” anatomical organization, with various nuclei and distinct chemical boundaries. However, the functional implications of this organization are unknown. Dr. Lesicko’s experiments aim to determine whether this modularity underlies distinct streams of information processing in the inferior colliculus. Using a combination of two-photon calcium imaging, clustering analysis, optogenetics, and behavioral assays in mice performing a behavioral task, the work will examine distinctions in neural activity and mechanisms for auditory and somatosensory signaling in the inferior colliculus.

GABAergic circuit interactions within the behaving mouse dLGN Bickford, Martha E (contact) Guido, William University Of Louisville 2017 Active
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The flow of visual information from the retina to the dorsal lateral geniculate nucleus (dLGN) in the brain is regulated by behavior, but the dynamic neural circuits governing these interactions have yet to be studied in awake, behaving animals. Martha Bickford and team are determining how inhibitory elements of the dLGN coordinate in behaving animals to modulate visual responsiveness and firing mode. They plan to use both optogenetic and chemogenetic techniques to target specific activation or inactivation of inhibitory circuits in dLGN, observing both dLGN neuron responses and measures of behavioral state in the mice. By developing these methods in vivo, the group aims to develop a novel approach to answering a wide variety of questions regarding thalamic function.
Generating a formal set of collaborative standards for sharing behavioral data and task designs to enable reproducibility in neuroscience Edwards, Stephen Anthony; Kepecs, Adam (contact) Cold Spring Harbor Laboratory 2019 Active
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Different laboratories use different behavioral systems, hardware, and software, which makes it difficult to standardize, communicate, and replicate experiments. Dr. Kepecs et al. have led the creation of a laboratory consortium to address this problem by developing requirements for behavioral data formats and an open source software suite for editing, executing, and visualizing behavioral tasks. They will also engage the scientific community to promote the adoption of these standards and tools.

Genetic analyses of complete circuit formation in Caenorhabditis elegans Cook, Steven Jay Columbia Univ New York Morningside 2017 Active
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Using the model system C. elegans, which has a simple, well characterized nervous system, Dr. Cook will develop new tools to create an exquisitely detailed map of a circuit in live animals and reveal the genetic factors that orchestrate assembly of a complete neural circuit.
Graph theoretical analysis of the effect of brain tumors on functional MRI networks Holodny, Andrei I Makse, Hernan (contact) City College Of New York 2016 Active
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Individuals with brain tumors often recover function after the brain has adapted to the tumor. It is difficult, however, to predict which patients will recover based solely on the location of the tumor. Makse and his colleagues propose to develop a software tool to analyze a neuroimaging database of 1500 patients with glial tumors in order to discover the relationship between brain disease states and tumor location. This project will extend and test their theoretical model of how the brain adapts to recover lost functions in the presence of a brain tumor. The researchers’ new software tool will also aid in the understanding, diagnosis, and treatment of brain disorders thought to be due to disruptions of brain connectivity, including Alzheimer's disease, ADHD, stoke and traumatic brain injury.
High SNR Functional Brain Imaging using Oscillating Steady State MRI NOLL, DOUGLAS UNIVERSITY OF MICHIGAN AT ANN ARBOR 2018 Active
  • Human Neuroscience
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To improve the spatial resolution of functional magnetic resonance imaging (fMRI), researchers often turn to higher magnetic field strength systems. While these systems can provide images of better quality, they require costly investment and maintenance. Dr. Douglas Noll and a team of investigators propose to improve fMRI techniques by developing a new method - Oscillating Steady State (OSS) Acquisition, for collecting MRI and fMRI data. This approach reuses magnetization to improve the signal-to-noise ratio, achieving a signal gain that is roughly equivalent to the shift from 3T to 7T, but without the practical and technical challenges and additional costs. If successful, the method can be widely and quickly disseminated to the neuroimaging community to upgrade existing 3T systems with reduced variability, noise, and improved sharpness of the images without increasing the cost of instrumentation.

High speed, high precision volumetric multiphoton neural control Adesnik, Hillel UNIVERSITY OF CALIFORNIA BERKELEY 2018 Active
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Dr. Adesnik will lead an interdisciplinary team of neuroscientists, engineers, and computer programmers to use holographic control of lasers to upgrade the speed, scale, and resolution of current multiphoton neural control systems to manipulate circuits using optogenetics. This will allow researchers to precisely stimulate and record the activity of many neurons that control thinking, feeling, and behavior from deep inside the brain. As part of this, they will engineer high potency, ultrafast opsin genes for stimulating neurons with light. This may help researchers to precisely explore the circuit activity behind neurological and neuropsychiatric disorders.

High-density microgrid development for human neural interface devices Cleary, Daniel R University Of California, San Diego 2019 Active
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Brain-computer interfaces (BCI) show promising potential in treating symptoms of various brain diseases. A collaborative group at the University of California, San Diego, has developed a high-density array of microgrid electrodes that are thin, non-destructive, and sit lightly on the surface of the brain, for improved decoding and resolution of neural activity. This study will implement this technology to study cortical physiology and organization in the rat somatosensory cortex. Dr. Cleary aims to test the capabilities of these surface microgrids for discriminating cortical columns in the rat “barrel cortex,” representing innervation of the whiskers. He also will study how surface stimulation of the cortex affects neural activity in different layers of the cortex, initially in rats and subsequently in human neurosurgical patients. This work may improve BCI technology, providing additional treatment strategies for various brain diseases.

Human Agency and Brain-Computer Interfaces: Understanding users? experiences and developing a tool for improved consent Goering, Sara (contact) Klein, Eran University Of Washington 2018 Active
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Agency, our ability to act and experience a sense of responsibility for our actions, is central to individual identity and societal conceptions of moral responsibility. Neural devices are currently used to treat some brain disorders, such as Parkinson’s disease, and are being developed to treat others such as depression and obsessive-compulsive disorder, yet their use raises important ethical concerns about potential effects on agency. Dr. Goering, Dr. Klein and their team will investigate agency in individuals receiving brain computer interface devices for sensory, motor, communication, and psychiatric indications. They aim to build a user-centered neural agency framework, and, ultimately, to enhance the informed consent process by developing a communication tool that patient participants might use to better understand and discuss potential changes in agency associated with use of neural devices.

Human Neocortical Neurosolver Hamalainen, Matti Hines, Michael L Jones, Stephanie Ruggiano (contact) Brown University 2016 Active
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Magnetoencephalography (MEG) and electroencephalography (EEG) are the leading non-invasive methods for recording human brain activity with millisecond resolution. However, it is still extremely difficult to interpret the underlying cellular and circuit-level sources of these large-scale signals without simultaneous invasive recordings. This challenge limits the use of MEG and EEG in the development of treatments for neural disorders. Jones and her colleagues propose a new software tool, called the Human Neocortical Neurosolver (HNN), that allows researchers to develop and test hypotheses about the origin of non-invasively measured human brain signals obtained with MEG and EEG. The insights obtained with the HNN tool will be helpful in understanding the underpinnings of neurological and psychiatric diseases, such as autism and schizophrenia.
Identifying, manipulating, and studying a complete sensory-to-motor model behavior circuit STOWERS, LISA SCRIPPS RESEARCH INSTITUTE 2018 Active
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Sensory stimuli can elicit many types of behaviors, yet it remains unclear how this occurs. Dr. Stowers’ project aims to improve understanding of the link between sensory input and behavioral changes. Her team will look at a well-defined behavioral response in mice and determine the complete neural circuit responsible from olfactory input to muscle. Once the circuit is identified, Dr. Stowers’ group will study the circuit’s neuronal activity patterns to determine how behavioral information is coded within the brain. This project will help advance our understanding of how the brain converts stimuli from the environment into behavioral changes.

Illuminating Neurodevelopment through Integrated Analysis and Vizualization of Multi-Omic Data Hertzano, Ronna (contact) White, Owen R University Of Maryland Baltimore 2018 Active
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Molecular and cellular neuroscientists often lack the training in computer programming to fully explore “-omics” data common in the BRAIN Initiative. Drs. Hertzano and White will implement analytic software for visualization and interactive genome browsing of gene expression and RNA-seq data, including simple and complex cross-dataset analysis. These tools will be made available in the BRAIN Initiative funded Neuroscience Multi-Omic Data Archive (NeMO) which hosts multi-omic data. The software will provide an easy-to-use web-based work environment for visualization and analysis of multi-modality and multi- omic data, interrogation of relationships between epigenomic signatures and gene expression, and integration of analytical techniques for multivariate analysis, gene co- expression and other analyses.

Imaging Brain Function with Biomechanics Patz, Samuel (contact) Sinkus, Ralph Brigham And Women's Hospital 2019 Active
  • Human Neuroscience
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Functional magnetic resonance imaging (fMRI) measures the blood-oxygenation-level dependent (BOLD) response to neuronal activity. Although it has become a ubiquitous tool for high spatial resolution mapping of whole-brain function, the quest for breaking the barrier on temporal resolution has never stopped. Drs. Patz, Sinkus, and team will develop a novel technique, functional magnetic resonance elastography (fMRE), that measures brain tissue stiffness change in response to neural activity. This state-of-the-art, ground-breaking non-invasive imaging technology is poised to provide an order of magnitude improvement of temporal resolution over fMRI, which could potentially provide a new window for assessing brain circuits and function.

Imaging Human Brain Function with Minimal Mobility Restrictions Garwood, Michael G University Of Minnesota 2017 Active
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  • Human Neuroscience
Conventional magnetic resonance imaging (MRI) from whole-body magnets has become a critical tool for human neuroscience research, but there are limitations to both their usability and technical requirements. High-quality MR images typically require large magnets that maintain a static magnetic field, but in a multi-institution effort led by Michael Garwood, researchers are developing a portable MR imaging prototype that collects high-quality images with a small, light-weight magnet that also permits some degree of freedom of movement. This technological development has the potential to revolutionize MRI approaches, making it possible to collect high-quality MR images by improving scanner portability: bringing the scanner to human subjects and patients, rather than the other way around.
Imaging the D2/A2A Heterodimer with PET Mach, Robert H University Of Pennsylvania 2018 Active
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Dr. Robert Mach and team propose to develop PET imaging agents that have a potential to visualize dimeric dopamine D2/adenosine A2A receptors. This proof-of-concept study could provide a new methodology for imaging G protein coupled receptors (GPCR) heterodimers in vivo with PET. Current methods for imaging single GPCRs are not adequate to fully understand the complexity of brain function, thus new strategies are needed to image them to understand the change in receptor mechanism that can occur with disease.

Impact of cortical feedback on odor concentration change coding Shusterman, Roman Smear, Matthew C (contact) University Of Oregon 2017 Active
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The brain uses both feedforward and feedback connections across many of its neural systems, but the computational role of feedback in these circuits is often unclear. Matthew Smear and Roman Shusterman are investigating cortical feedback neurons in the olfactory system through novel optogenetic strategies that can identify, record, and silence these neurons. After first determining the feedback signals that an olfactory cortical area sends to the olfactory bulb in awake mice, the team will investigate the necessity of that feedback in odor sensitivity. In the long-term, the optogenetic silencing method proposed here has the potential to facilitate a greater understanding of the role of top-down feedback in neuronal computation.
Improving Human fMRI through Modeling and Imaging Microvascular Dynamics Polimeni, Jonathan Rizzo Massachusetts General Hospital 2016 Active
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  • Human Neuroscience
Functional Magnetic Resonance Imaging (fMRI)—the most common technique for mapping whole brain function in humans—is based on tracking changes in blood flow that occur during brain activity. However, the temporal and spatial resolutions for this technique are fairly low. Polimeni and his colleagues will improve fMRI’s specificity by using 2-photon microscopy to create new models of the way blood flows in the brain and linking those models with highly detailed maps of human microvascular anatomy. A better understanding of how microvascular dilations and blood flow changes impact the underlying neural signals will help neuroscientists better understand fMRI signals and enable them to map human brain function at a finer scale than what is currently possible.
In Vivo Imaging of Local Synaptic Neuromodulation by Dopamine Evans, Paul Robert Max Planck Florida Corporation 2018 Active
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Dopamine is a powerful neurotransmitter that facilitates memory formation and underlies reward-related behaviors, but current techniques to assess dopamine signaling in vivo lack sufficient specificity and spatiotemporal resolution. Evans will develop new fluorescent sensors for dopamine receptors and apply them to investigate the molecular mechanisms that underlie learning in mice in vivo. The biosensors will be used to visualize the dynamic activity of specific dopamine receptors in vitro, before they are virally expressed in the motor cortex in behaving mice. Employed during motor learning, these sensors should generate a sub-micron scale map of how dopamine receptor subtypes modulate long-term structural plasticity of cortical dendritic spines. The results could help shed light on how dopaminergic modulation correlates with structural and functional plasticity.
Informing Choice for Neurotechnological Innovation in Pediatric Epilepsy Surgery Illes, Judy (contact) Mcdonald, Patrick University Of British Columbia 2018 Active
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More than 500,000 children in the US and Canada suffer from epilepsy and 30% of these children continue to experience seizures despite being treated with anti-seizure medication. Unmanaged, epilepsy can result in cognitive decline, social isolation, and poor quality of life, and has substantial economic impact on families and society. Novel approaches for treating epilepsy such as vagal nerve stimulation and responsive neurostimulation are being developed, but this work has been conducted predominately in adults and the outcomes of these trials are often not clearly generalizable to children. In this project, Drs. Illes and McDonald will explore ethical issues confronting families and clinicians when considering new treatment options for drug-resistant epilepsy in children. They aim to develop, evaluate, and deliver patient-directed resources in the form of infographics and informational materials and videos, and clinician resources for family decision-making, clinician counseling, and care.

Input-specific imaging and manipulation of synaptic plasticity underlying social memory Phillips, Mary L Max Planck Florida Corporation 2019 Active
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In an effort to improve our understanding of how synaptic plasticity contributes to social memory, Dr. Phillips aim to create a tool to modulate synaptic plasticity in specific circuits during behavior. Using advanced imaging techniques and various innovative biochemical assays, she plans to create a photo-activatable inhibitor of presynaptic plasticity and will use this tool to understand the circuitry of social memory. The researcher will develop constructs of a photo-activatable PKA inhibitor and screen the constructs using 2-photon fluorescence lifetime imaging in HeLa cells. The optimized inhibitor constructs will then be expressed in the dCA2-vCA1, vCA1-PL, and PL-dPAG projections in mice and used to block presynaptic plasticity during social learning in either aggressive or neutral contexts.  Successful development of these tools will enable investigation of neural circuitry to better our understanding of behavior and neuropsychiatric diseases.

Integrated fMRI Methods to Study Neurophysiology and Circuit Dynamics at Laminar and Columnar Level Chen, Wei University Of Minnesota 2016 Active
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  • Human Neuroscience
Functional MRI is a powerful technique for mapping functional brain activity. However, its low spatial resolution prevents accurate mapping of activity at the scale of cortical layers. Another long-standing limitation of fMRI has been the inability to study how neural inhibition impacts neural dynamics and networks. Chen and his colleagues propose to integrate ultrahigh-resolution high-field fMRI with the selective stimulation of groups of inhibitory neurons to study correlates of fMRI signals in neural circuits. This project has the potential to bring clarity to the relationship between structure and function at the level of individual neuronal layers, as well as shed light on the dynamics of neural activity.
Integrative Analysis of Long-range Top-down Cortical Circuit for Attentional Behavior Morishita, Hirofumi Icahn School Of Medicine At Mount Sinai 2017 Active
  • Integrated Approaches
Thought to be driven by regions in frontal cortex, attentional behavior underlies many core cognitive behaviors, yet its precise neural circuit mechanisms remain poorly understood. Hirofumi Morishita and collaborators plan to investigate the role of cortical circuits between the frontal and sensory cortex while dynamically modulating attentional behavior in mice. Through an innovative combination of technologies including viral mapping, electrophysiology, fiber photometry, miniscope imaging, and optogenetics, the team plans to identify when these circuits are activated, how they affect attentional behavior, and whether modulation of these circuits can improve attentional behavior. Having a strong basis for the causal role of this frontal-sensory cortical circuit will pave the way for analysis of other circuits in the brain, as well as potential examination of this circuit in pre-clinical applications.
Integrative Functional Mapping of Sensory-Motor Pathways Dickinson, Michael H (contact) Holmes, Philip J Mann, Richard S Wilson, Rachel California Institute Of Technology 2014 Complete
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Dr. Dickinson will lead an interdisciplinary team to study how the brain uses sensory information to guide movements, by recording the activity of individual neurons from across the brain in fruit flies, as they walk on a treadmill and see and smell a variety of sights and odors.
Intercellular TWEAK/Fn14 Cytokine Signaling in Sensory-Dependent Circuit Refinement Cheadle, Lucas M Harvard Medical School 2019 Active
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Neurodevelopmental disorders can arise from impairments in sensory-dependent refinement or strengthening of synapses during postnatal brain development. However, treatment strategies focused on addressing such impairments lack an advanced understanding of the cellular and molecular mechanisms of this process. Building on prior results showing that expression of the gene Fn14 is driven by visual experience and encodes a receptor required for synaptic refinement, Dr. Cheadle aims to use slice electrophysiology and bioinformatics to study how microglia-to-neuron signaling is involved in refinement via examining the role of TWEAK, an Fn14 receptor ligand, in healthy and neurodevelopmentally-impaired mice. The results may offer insights into the development of treatments for neurodevelopmental disorders.

Interneurons differentially regulate discrete pathways from ventral hippocampus Donegan, Jennifer University Of Texas Hlth Science Center 2019 Active
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Hippocampal microcircuits include excitatory pyramidal cells, which integrate information and signal to downstream brain regions, and inhibitory interneurons, which function locally to regulate pyramidal cell activity. Circuit dysfunction in the ventral hippocampus (vHipp) has been associated with various brain disorders. Dr. Donegan will use techniques including mammalian GFP reconstitution across synaptic partners (mGRASP), fiber photometry, in vivo electrophysiology, and optogenetics, to test the hypothesis that different types of interneurons in the vHipp differentially regulate the function of ventral hippocampus pyramidal cells depending on their projection target. She will also test whether vHipp microcircuit anatomy and function are altered by chronic stress, shedding light on the potential link between circuit dysfunction in the hippocampus and brain disorders.

Intraoperative studies of flexible decision-making Baltuch, Gordon H (contact) Gold, Joshua I University Of Pennsylvania 2017 Active
  • Human Neuroscience
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Even relatively simple sensory-motor decisions, such as goal-directed eye movements, exhibit sufficient flexibility and nuance to be considered a “window on cognition.” Gordon Baltuch’s team will leverage the unique opportunity provided by surgical treatment of Parkinson’s disease using deep brain stimulation, to study decision-making in the human brain at the single-neuron level. The team will simultaneously measure behavioral response time and accuracy (by asking neurosurgical patients to select a visual stimulus via eye movements) while performing brain electrophysiology. Additionally, they will conduct parallel monkey and human studies that, unlike Parkinson’s studies alone, will distinguish normal versus disrupted mechanisms in the Parkinson’s -affected brain. This project may yield a sustainable research program that probes not only neural mechanisms of decision-making, but also potential causes of, and remedies to, cognitive side effects associated with deep brain stimulation.
Invasive Approach to Model Human Cortex-Basal Ganglia Action-Regulating Networks Pouratian, Nader University Of California Los Angeles 2016 Active
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Circuits between the frontal cortex and basal ganglia (BG) may support the ability to suppress actions once additional information becomes available to indicate the most appropriate decision, but few studies provide the necessary spatial and temporal resolution to investigate this mechanistically. Dr. Pouratian’s group will utilize deep brain stimulation (DBS) electrodes in Parkinson’s patients to record from cortical and BG regions in multiple action-suppression tasks. In addition to investigating unit and local field potential activity during tasks, the group will use DBS coupled with functional imaging to stimulate the circuits and measure effects on brain activity, eventually developing a computational model of action suppression. Aside from informing the basic science of this circuitry, this project could expand upon how DBS influences brain networks for action, which could improve therapeutic use in various disorders.
Investigating information processing in parallel circuits that link external chemical signals to social behavior Meeks, Julian P Ut Southwestern Medical Center 2017 Active
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Understanding the contributions of sensory circuits to perception, emotions, and behavior is a critical task in neuroscience, but for the accessory olfactory system in mice – an ideal-model sensory circuit – technical barriers have prevented a thorough investigation. Julian Meeks’ team aims to overcome these barriers by expanding the capacity to measure olfactory chemosensory encoding and integration ex vivo through stereolithography and volumetric imaging methods. They also plan to evaluate how the accessory olfactory system sorts information in the olfactory bulb and its immediate downstream targets through retrograde labeling and multi-site multi-electrode recordings. Success with this ambitious project will improve our understanding of the mechanisms by which mammalian neural circuits decode environmental information and use that information to guide behaviors.
Investigating the hypocretin to VTA circuit in memory consolidation during sleep Borniger, Jeremy Stanford University 2018 Active
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Brain-computer interfaces and neuroprosthetics have provided a significant benefit to patients with cervical spinal cord injuries. However, current technology is limited in its abilities to allow the user to control how much force is exerted by the prosthesis and to provide sensory feedback from the prosthetic hand. In a public-private collaboration with Blackrock Microsystems, Dr. Boninger and colleagues are looking to improve the dexterity of neuroprostheses by incorporating microstimulation of the somatosensory cortex. This stimulation could provide tactile feedback to the user and hopefully allow the user to better control the force applied. Ultimately, this approach will improve the dexterity and control of prosthetic limbs used by patients with spinal cord injuries.

Investigating the neurocircuitry of sleep duration regulation Fu, Ying-hui University Of California, San Francisco 2018 Active
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Gene variations have been identified (called ADRB1 and DEC2) that enable individuals expressing these variations to sleep fewer hours per day without health detriments. Fu’s team seeks to demonstrate that there are unique neurocircuits for sleep duration/efficiency, separate from sleep/wake-promoting circuits. First, the team will systematically search for ADRB1-positive and DEC2-positve cells in the brains of transgenic mice. To confirm that ADRB1/DEC2-expressing networks are critical for regulating sleep duration/efficiency, they will pharmacogenetically and optogenetically manipulate ADRB1/DEC2-expressing neurons/circuits and evaluate the resulting effects on sleep. To understand mechanistic relationships, they will examine ADRB1/DEC2-positive cell activities while monitoring sleep state with EEG/EMG recording. This project may lead to a better understanding of the neurocircuitry of sleep regulation.
Investigating the Role of Neurotensin on Valence Assignment During Associative Learning in the Basolateral Amygdala Olson, Jacob Michael Massachusetts Institute Of Technology 2017 Active
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Dr. Olson will systematically identify, manipulate, and characterize the neural projections that release the neuropeptide neurotensin to the basolateral amygdala during behavior conditioning tests in mice to identify a new circuit that regulates associative learning.
Is the Treatment Perceived to be Worse than the Disease?: Ethical Concerns and Attitudes towards Psychiatric Electroceutical Interventions Cabrera Trujillo, Laura Yenisa Michigan State University 2018 Active
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The NIH BRAIN Initiative aims to catalyze novel tools and technologies to modulate brain circuit function, paving the way for new treatment options for brain disorders. However, such interventions also have the potential to cause unintended changes in aspects of cognition, behavior, and emotion. These changes, in turn, raise concerns regarding autonomy, personal identity, and capacity for informed consent. In this study, Dr. Cabrera Trujillo and her team will study ethical concerns, beliefs, and attitudes about the use of novel bioelectric approaches among clinicians, patients, and the broader public. The work will provide stakeholder perspectives that will be valuable for informing the responsible development and use of these novel neurotechnologies.

Lagging or Leading? Linking Substantia Nigra Activity to Spontaneous Motor Sequences Adams, Ryan Prescott Datta, Sandeep R Sabatini, Bernardo L (contact) Harvard Medical School 2015 Complete
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One of the goals of the BRAIN Initiative is to understand how the brain generates behaviors. These researchers are utilizing a novel 3D machine vision technology to automate classification of spontaneous behavior when freely-moving mice are confronted with stimuli; they are then correlating that information with dense recordings of neural activity in key regions of the brain implicated in movement disorders. Researchers are then manipulating the activity of specific neurons in this brain region with light to test their role in the animal’s behavior. Dr. Sabatini and colleagues offer an innovative ‘grammatical’ structure to understanding how the brain produces complex, systematic behavior.
Large-scale monitoring of sensory transformations in the mammalian olfactory system Burton, Shawn Denver University Of Utah 2017 Active
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Dr. Burton will leverage recent enhancements in calcium indicators to image pre- and post-synaptic neural activity simultaneously in the mammalian olfactory system, gaining insight into how sensory information is transformed as it moves through a neural circuit.
Large-scale Network Modeling for Brain Dynamics: Statistical Learning and Optimization Luo, Xi Brown University 2016 Active
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Functional MRI (fMRI) is a useful technique for examining brain-wide networks involved in tasks that involve perceiving stimuli and behaviorally responding to those stimuli. Luo and his colleagues are applying machine learning approaches for modeling whole-brain networks using fMRI and behavioral response data captured during the performance of specific tasks. The algorithms the team develops will facilitate the analysis of a wide array of neuroimaging and behavioral data, which may lead to the discovery of pharmacological targets for treating neurological and psychiatric disorders.
Large-scale recording of population activity during social cognition in freely moving non-human primates DRAGOI, VALENTIN et al. UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON 2018 Active
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Humans are social creatures. Positive interactions with others, such as cooperation and altruism, are important for our species’ health and survival, but not much is known about the mechanisms underlying these behaviors. Drs. Aazhang, Dragoi, and Wright plan to identify specific brain regions involved in social cognition and investigate how brain activity changes as animals determine whether to cooperate with each other. The team will record brain activity in freely interacting monkeys as they participate in social cognition tasks, including working with one another to obtain food. Increased knowledge about complex social behaviors may help understand collective interactions among individuals and could improve treatments for certain mental health disorders.

Learning spatio-temporal statistics from the environment in recurrent networks Brunel, Nicolas Shouval, Harel Zeev (contact) University Of Texas Hlth Sci Ctr Houston 2016 Active
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Learning new tasks and interacting with new environments leads to changes in the dynamics of brain circuits. The ability of animals to incorporate the statistical properties of the environment into decision-making brain circuits is necessary for survival. Shouval and his colleagues plan to develop a theoretical model for how brain circuits implement these statistics. This model may provide novel insights into the basis of a variety of neurophysiological processes, including learning and memory.
Leveraging ethical dissension among capacity, beneficence and justice in clinical trials of neurotherapeutics in the severely disabled: lessons from schizophrenia Davis, Rachel A Gault, Judith Morse (contact) Saks, Elyn R. University Of Colorado Denver 2019 Active
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Individuals with severe, disabling, chronic mental illness, such as treatment-refractory schizophrenia/schizoaffective disorder (TRS), have often been excluded from research, leading to challenges in developing treatment for their illnesses as well as access to that treatment. Here, Dr. Judith Gault will examine the ethical issues that will lay a foundation for conducting clinical research in TRS patients who have traditionally been excluded in studies. These ethical principles will include transparency, accessibility and safety of clinical trials testing neurosurgical intervention in TRS patients who are in urgent need of effective novel interventions. The team will explore the ethical implications of excluding individuals based on their capacity to consent, surgical risks, and severity of symptoms for a planned clinical trial to treat TRS. Successful completion of the project could revolutionize our understanding of how to overcome research disparities among severely disabled individuals by improving transparency, accessibility, and safety of clinical trials.

Lightweight, Compact, Low-Cryogen, Head-Only 7T MRI for High Spatial Resolution Brain Imaging Foo, Thomas (contact) Shu, Yunhong Xu, Duan General Electric Global Research Ctr 2018 Active
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Non-invasive magnetic resonance imaging (MRI) is an important tool for our understanding of the human brain. However, ultra-high field magnets are hampered by their massive size and challenging installation, limiting their accessibility to researchers and clinicians. Dr. Thomas Foo and a team of investigators propose the development of a 7T MRI system with high-performance head gradients, delivering a head-only, high-resolution MRI system that is significantly smaller and lighter in comparison to existing ultra-high field systems. The group will design, optimize, and validate a head-only 7T MRI system, piloting the system in healthy volunteers to assess the quality of the structural, functional, and metabolic data. The proposed work has the potential to open a range of scientific and clinical applications that cannot currently be achieved with existing instrumentation.

Linking neuronal, metabolic, and hemodynamic responses across scales Ghose, Geoffrey M University Of Minnesota 2018 Active
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Previous work on blood oxygenation level dependent (BOLD) signals underlying functional magnetic resonance imaging (fMRI) has typically focused on improvements in spatial resolution. Emerging data suggest that when fast fMRI designs are used, rich information can be extracted from the temporal aspects of BOLD fMRI. Dr. Ghose and colleagues will simultaneously measure and compare neuronal, metabolic, and hemodynamic responses that underlie the BOLD signal as a function of stimulus strength, behavioral state, and brain network state using fast optical and MR imaging techniques. By integrating imaging and stimulation technologies that span the scale from neurons to voxels across species, this multi-modal approach will enable temporally precise inferences to be drawn regarding the relationship between neuronal activity and fMRI measurements.

Linking Plasticity of Hippocampal Representation across the Single Neuron and Circuit Levels BASU, JAYEETA et al. NEW YORK UNIVERSITY SCHOOL OF MEDICINE 2018 Active
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<p>Functional circuits between the entorhinal cortex and hippocampus are known to play a major role in spatial navigation and episodic memories. To develop a theoretical model of studying neural plasticity at both the single cell and circuit levels, Drs. Basu and Clopath will target specific cortico-hippocampal circuits using&nbsp;in vivo&nbsp;two-photon calcium imaging, slice electrophysiology, and optogenetic manipulation, in newly-developed transgenic mice. The knowledge gained from these experiments will aid in the understanding of neural circuits of functional memory and may influence treatments for diseases with neurological dysfunctional states, such as Alzheimer’s disease.&nbsp;</p>

MACHINE LEARNING APPROACHES FOR ELECTROPHYSIOLOGICAL CELL CLASSIFICATION Barth, Alison L Carnegie-mellon University 2017 Active
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Recordings of neural spike activity produce high-density, temporally precise patterns of neural firing that researchers aim to deconstruct into meaningful accounts of information processing in the brain. As the amount of generated data increases, neuroscientists need to decode more information than neuronal firing – they must be able to identify which specific cell-types are firing. Alison Barth is teaming up with computer scientists to develop a machine-learning classifier that can differentiate between inhibitory neuron subtypes in somatosensory cortex by using information from features such as rate of spontaneous firing, response to stimulation, and covariance of activity. By developing algorithms for cell identification that can identify specific neuron subtypes from spike train data in vivo, this project has the potential to build bridges between local circuit computations and cognitive processes.
Manifold-valued statistical models for longitudinal morphometic analysis in preclinical Alzheimer's disease (AD) Johnson, Sterling C Singh, Vikas (contact) University Of Wisconsin-madison 2016 Active
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In light of the profound public health issues Alzheimer’s disease (AD) represents, there is a tremendous need for methods to identify the onset of the disease as early as possible. Singh and his colleague propose to develop novel methods for analyzing Cauchy deformation tensors (CDTs) in brain images. These methods will enable the identification of structural changes in healthy midlife adults that are predictive of AD onset. The proposed analysis will be conducted on the largest preclinical AD cohort assembled to date and will help inform how telltale clinical biomarkers of AD emerge in asymptomatic individuals at risk for the disease. These preclinical biomarkers may be used in the design of clinical trials for new therapies.
Mapping cerebellar granule cell function with novel genetic and optical tools Broussard, Gerard Joey Princeton University 2019 Active
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Small, tightly-packed granule cells (GrCs) in the cerebellum have been associated with sensory and motor events, but their specific roles remain unclear due to their close packing.  Dr. Broussard aims to precisely record from and perturb GrCs and measure the resulting effects on neural firing patterns and activity in mice. The researcher will develop a spike-counting method for genetically encoded indicators by optimizing the kinetics of the calcium sensor GCaMP. After developing a cleared skull preparation to access the full posterior cerebellum in mice, the new indicator will be used to map the neocortical drivers of GrC activity across the cerebellum, and rodent behavioral tasks will be used to disambiguate sensory, motor and internal-state contributions to granule cell activity patterns. Better knowledge of GrCs activity will further our understanding of neural circuits that guide sensory processing and plays roles in neurological disorders.

Mapping of spatiotemporal code features to neural and perceptual spaces RINBERG, DMITRY et al. NEW YORK UNIVERSITY SCHOOL OF MEDICINE 2018 Active
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Sensory systems neuroscience investigates how stimuli are represented by the activity of populations of neurons, as well as how neural circuits process this information, resulting in behavioral outcomes. After varying patterns of optogenetic stimulation and recording both neural activity and behavioral output, Drs. Rinberg and Panzeri will develop a mathematical model of neural coding for odor discrimination in mice. Their model may determine the specialized spatiotemporal neural code involved in olfactory processing which could be further applied to other neural circuits.

Measuring, Modeling, and Modulating Cross-Frequency Coupling Eden, Uri Tzvi Kramer, Mark Alan (contact) Boston University (charles River Campus) 2018 Active
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Cross-frequency coupling (CFC) is a phenomenon through which brain rhythms of different frequencies (fast vs. slow oscillations) coordinate to enable efficient communication between and among neural networks. Current methods measure a single type of CFC related to a given research question, but do not necessarily account for different interactions or combinations between phase and amplitude in fast and slow frequency bands. Drs. Kramer and Eden will develop a more general statistical inferential framework to estimate CFC in rats by creating a method to acquire real-time phase and amplitude data for estimation of CFC to accommodate dynamic manipulations. The team will incorporate computational modeling studies to simulate CFC between the amygdala and the frontal cortex and test via in vivo experiments. This framework will allow future users to explore the basis of network communication in the brain and evaluate the causal role of cross-frequency coupling.

Mechanisms of Active Sensing in Drosophila Suver, Marie New York University School Of Medicine 2019 Active
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To process information about the world, the nervous system must distinguish external stimuli from internally generated sensory stimuli, but the mechanisms underlying the cellular basis of internally generated sensation and movement are not well understood. Here, Dr. Suver plans to develop a small circuit model of this process using the antennae of the fruit fly as a model system. Using electrophysiological recordings, optogenetics, and immunohistochemistry, she will develop the neural circuits controlling and sensing antennal movement as a cellular model for studying principles of active sensing. The insights gained from a tractable genetic circuit model may improve understanding of active sensation, as well as how these mechanisms might fail in disease.

Mechanisms of Information Routing in Primate Fronto-striatal Circuits Womelsdorf, Thilo Vanderbilt University 2019 Active
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The brain can rapidly reconfigure its activity to switch between goals and tasks, but the neural mechanisms underlying this complex process are not well understood. Based on evidence that changes in routing are driven by quick bursts of neural activity, Dr. Thilo Womelsdorf and his team will develop new analysis tools to investigate the mechanisms of routing information in neural circuits during goal-directed behavior. After first detecting the bursts, the group will characterize how they coordinate within one functional network, then address the impact of that coordination on information flow. The development of these analytical tools to study complex cognition within a rigorous framework has the potential to create a seamless pipeline for translation between experimental findings and analytical solutions.

Mechanisms of neural circuit dynamics in working memory Bialek, William Brody, Carlos D (contact) Seung, Hyunjune Sebastian Tank, David W Wang, Samuel Sheng-hung Witten, Ilana Princeton University 2014 Complete
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Dr. Brody and his colleagues will study the underlying neuronal circuitry that contributes to short-term "working" memory, using tools to record circuit activity across many brain areas simultaneously while rodents run on a track-ball through virtual mazes projected onto a screen.
Mechanisms of neural circuit dynamics in working memory anddecision-making Brody, Carlos D (contact) Pillow, Jonathan William Seung, Hyunjune Sebastian Tank, David W Wang, Samuel Sheng-hung Witten, Ilana Princeton University 2017 Active
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Intense research efforts have focused on understanding working memory and decision-making, but technical and theoretical limitations have prevented a thorough understanding of these cognitive processes. Building on a previous BRAIN award, Carlos Brody and a team of experts are now aiming to outline a multi-brain-region, biophysical circuit model of the mechanisms that underlie working memory and decision-making. While mice complete a working memory task, the group will employ a variety of advanced imaging methods and optogenetic inactivation approaches to inform computational methods of incorporating these data into an integrative circuit model of the central nervous system. This combination of innovative methods can provide a mechanistic understanding of how the brain works with information.
Mechanisms of Rapid, Flexible Cognitive Control in Human Prefrontal Cortex Sheth, Sameer BAYLOR COLLEGE OF MEDICINE 2018 Active
  • Human Neuroscience
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The human brain can quickly “program” itself to adapt to novel situations, such as figuring out how to drive a rental car through a new city. Dr. Sheth and his colleagues plan to investigate how the brain assembles pieces of information into plans that help us manage new circumstances, and then develops a computational model of this learning. They will record from the brain’s dorso-lateral prefrontal cortex in patients with deep brain stimulation who are performing tasks to understand what information is being encoded and how it is processed. The project offers to provide a computational understanding of complex cognition. This may improve our understanding of cortical brain function and of neurological disorders that interfere with complex thinking.

Mechanisms underlying large-scale coordination of cortical activity during perceptual decisions Pinto, Lucas Princeton University 2019 Active
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Evidence suggests that both spontaneous and learned behaviors engage activity in various regions of the cortex. However, for perceptual decision-making, more complex and demanding tasks involve decorrelated cortical activity as a more distributed, widespread process throughout the cortex. Dr. Pinto aims to understand this phenomenon, using cutting-edge technology to study how distributed cortical acitivity mediates complex decision-making and the mechanisms of task-induced changes in large-scale cortical dynamics. The research will utilize two-photon calcium imaging, virtual reality behavioral tasks, pharmacogenetics, optogenetics, and modelling, increasing our understanding of the neural basis of decision-making.

Mechanisms underlying positive and negative BOLD in the striatum Shih, Yen-yu Ian Univ Of North Carolina Chapel Hill 2018 Active
  • Human Neuroscience
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A central assumption in blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging lies in the tight coupling between neuronal activity and vascular responses. To a large extent, data supporting this coupling has been based on cortical structures, but accumulating evidence suggests that the striatum exhibits a different pattern. Dr. Shih and colleagues will use a suite of cutting-edge neuroscience techniques, including optogenetics and chemogenetics, to selectively identify and target dopamine receptors, vasoactive neurotransmitters, and neuronal subtypes that underlie distinct positive and negative BOLD responses in the striatum. By using both multimodal modulation and recording techniques to simultaneously understand the vascular response to stimuli and the impact on BOLD, this project offers the potential to shed light on better understanding the function and role of the striatum in cognition and disease.

Mechanistic and causal basis of fMRI functional connectivity in non-human primates Rudebeck, Peter (contact) Russ, Brian E Icahn School Of Medicine At Mount Sinai 2018 Active
  • Human Neuroscience
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Neuroscience researchers and clinicians increasingly utilize connectivity measures of functional magnetic resonance imaging (fMRI) to better understanding circuit-level mechanisms of brain function and dysfunction yet establishing causal links between fMRI functional connectivity and neural activity remains challenging. Using non-human primates, Drs. Rudebeck and Russ propose a multi-dimensional approach that combines high-resolution multi-echo fMRI, high-density neurophysiology recordings, and pathway-specific manipulations of neural activity. Collectively, these measures will help to establish a causal understanding of how connectivity and neural activity measures are related to one another at rest and during cognitive tasks. By identifying the neural mechanisms underlying fMRI, this work will both aid basic research as well as inform therapeutic approaches that target distributed brain circuits.

Mechanistic dissection of the neural basis of the resting-state fMRI signal using multi-modal approaches Drew, Patrick James Zhang, Nanyin (contact) Pennsylvania State University-univ Park 2017 Active
  • Monitor Neural Activity
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  • Human Neuroscience
The neural basis of resting-state fMRI (rsfMRI) signal remains poorly understood. Particularly, poor understanding of cellular and circuit-level mechanisms underlying resting-state functional connectivity (RSFC) has hampered rsfMRI interpretation. Nanyin Zhang’s team will dissect the signal contributions of spiking activity from individual neuron populations. They will use multi-echo-rsfMRI (differentiates neural and non-neural rsfMRI signal components) to quantify RSFC by eliminating non-neural artifacts, and calcium-based fiber photometry to measure simultaneous neuronal and rsfMRI signals with neuron-type specificity. Finally, the group will optogenetically increase neuronal excitability and examine resulting RSFC and cortical-layer-specific electrophysiological signal changes. This project may enhance understanding of rsfMRI signal in humans, impacting brain disorder research.
Memory consolidation during sleep studied by direct neuronal recording and stimulation inside human brain FRIED, ITZHAK UNIVERSITY OF CALIFORNIA LOS ANGELES 2018 Active
  • Human Neuroscience
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Sleep is important for learning and memory, but the exact mechanisms of this process are not known. Dr. Fried and his team will examine the role of sleep in memory formation in humans by recording brain activity during sleep following learning tasks. Dr. Fried’s group will identify the sleep events, such as sleep stage or changes in firing activity, that show the strongest association with memory consolidation. They will also examine whether electrical or auditory stimulation during sleep improves memory performance compared to undisturbed sleep. Greater knowledge of these mechanisms may help in the development of treatments for people suffering from memory and/or sleep disorders. 

Mental, measurement, and model complexity in neuroscience Balasubramanian, Vijay Gold, Joshua I (contact) University Of Pennsylvania 2018 Active
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Three specific challenges for neuroscience data include: 1) identifying the relevant spatial, temporal, and computational scales in which the underlying information-processing dynamics are best understood, 2) identifying the best ways to design and select models to account for these dynamics, and 3) inferring what the data tells us about how the brain itself processes complex information. Drs. Gold and Balasubramanian will develop theoretical tools for understanding how the brain integrates information across large temporal and spatial scales, using definitions of complexity to facilitate the analysis and interpretation of complex neural and behavioral data sets. This formal, mathematical assessment of data complexity could be used by the community for other data-driven model building and for comparisons of existing neuroscience models.

Methodologically-Integrated Approaches Linking Cell Types to Neural Circuits and Function Callaway, Edward M Salk Institute For Biological Studies 2017 Active
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Cortical circuits in the mouse are relatively well understood, but the extent they generalize to phylogenetically higher species remains unclear. Edward Callaway and colleagues are developing a suite of methods that will record neurons in non-human primate cortex, to better understand principles and functions of neural circuits in this model organism. Through molecular, genetic, viral, and large scale optical and electrical tools - including high-density electrode arrays and two-photon calcium imaging, Callaway’s team will investigate the levels of selectivity at which visually-evoked activity can be linked to circuits in terms of their cell types, connections, and functions. This novel approach in macaque monkeys has the potential to characterize large ensembles of simultaneously recorded neurons in important ways, a critical step in understanding neural circuitry across species.
Methods from Computational Topology and Geometry for Analysing Neuronal Tree and Graph Data Mitra, Partha Pratim (contact) Wang, Yusu Cold Spring Harbor Laboratory 2016 Active
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The complex tree shapes of neurons are important for their role in neuronal circuitry, but they are mathematically challenging to characterize and analyze. Mitra and his colleagues are applying advanced methods from computational topology and geometry to classify neuronal structure and its role in the function of circuits. The resulting tools will be made available to neuroscientists studying normal and diseased brain circuitry.
Microscopic foundation of multimodal human imaging Dale, Anders M Devor, Anna (contact) University Of California San Diego 2016 Active
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  • Human Neuroscience
The computational properties of the human brain arise from an intricate interplay between billions of neurons of different types that are connected in complex networks. The hypothesis behind the project from Devor and her colleagues is that specific neuronal cell types have identifiable “signatures” in the way they contribute to large electrical signals that drive changes in the brain’s energy metabolism and blood flow. To investigate this hypothesis, the researchers will attempt to relate cell-type specific neural activity to metabolism and blood flow signals using parallel experiments in mice and humans. If successful, the proposed project will create a way to measure neuronal activity of known cell types from across the entire human brain, offering a significant enhancement to techniques such as functional MRI (fMRI).
Model behavior in zebrafish: characterization of the startle response Meserve, Joy Hart University Of Pennsylvania 2018 Active
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The startle response is disrupted (i.e., uncoordinated or weak) in several neurological and psychiatric disorders. Meserve will investigate the startle response using live imaging of neural activity in transparent larval zebrafish. The slc5a7 gene (required for acetylcholine synthesis) modulates the startle response in zebrafish, and human slc5a7 mutations are implicated in attention deficit disorder and major depression. This project will study slc5a7a’s role in neural circuit development and/or startle response. Circuit defects in slc5a7a mutants will be investigated via calcium imaging and whole-brain activity mapping of neurons known to be required for the startle response. Integrated studies on gene function, neural circuitry, and behavior will uncover the developmental stage and anatomical region where slc5a7a is required. These experiments may determine how slc5a7a promotes normal startle response, and contribute knowledge about how acetylcholine regulates behavior.
Models and Methods for Calcium Imaging Data with Application to the Allen Brain Observatory Buice, Michael Witten, Daniela (contact) University Of Washington 2018 Active
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Though calcium imaging permits single-cell observations in behaving animals, variation between trials and complexities in activity-dependent calcium dynamics and fluorescent read-out create challenging data analyses. Motivated by a large-scale, publicly-available repository of calcium imaging data obtained from mouse models at the Allen Brain Observatory, Drs. Witten and Buice will develop novel statistical models, methods, and software to improve analysis techniques comparing extracellular electrophysiology and calcium imaging recordings in the context of behavior. Creating new, open, online algorithms to interpret fluorescent traces of firing neurons and building models that account for variations in neuronal activity, could improve researchers’ ability to draw rigorous and replicable conclusions on the basis of calcium imaging data.

Motion Sequencing for All: pipelining, distribution and training to enable broad adoption of a next-generation platform for behavioral and neurobehavioral analysis Datta, Sandeep R Harvard Medical School 2019 Active
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Despite the ability of scientists to record from and modulate the activity of individual neurons and neuronal circuits, it has been difficult to translate those observations into a readout of behavior. Dr. Datta and colleagues have developed a technology called Motion Sequencing (MoSeq) that captures, in three dimensions, the behavior of a freely moving mouse and then, using machine learning, turns that data into standard “syllables” of behavior. While MoSeq could have broad applications for several research projects, the complex math makes it difficult for non-expert users to implement. This project will adapt the MoSeq system to make it more accessible for researchers and will provide a training course on how to set up and use MoSeq. This will enable a wider range of research projects to use the technology, which could improve our ability to study the effects of drugs or genetic and neuronal changes on behavior.

MRI CORTICOGRAPHY: DEVELOPING NEXT GENERATION MICROSCALE HUMAN CORTEX MRI SCANNER Feinberg, David Alan (contact) Liu, Chunlei Mukherjee, Pratik Setsompop, Kawin Wald, Lawrence L University Of California Berkeley 2017 Active
  • Monitor Neural Activity
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  • Human Neuroscience
The macroscopic scale of current magnetic resonance imaging (MRI) scanners makes it challenging to link neural circuitry to human cognition and behavior. David Feinberg and his team are developing MR Corticography (MRCoG), a new tool for studying neuronal circuitry that improves resolution by an order of magnitude, making it possible to visualize cortical layers and microcircuit columns throughout the whole brain. By expanding on scanner hardware and image acquisition software that Feinberg has previously developed, the team intends to improve image sensitivity while reducing sources of signal distortion. With these tools, they plan to explore the clinical potential of MRCoG in patients with epilepsy and autism spectrum disorder. MRCoG has the potential to be a major advance in human neuroscience, providing researchers with a tool to connect cortical visualization to clinical and cognitive neuroscience.
Multi-context software for robust and reproducible neuroscience image analysis Papademetris, Xenophon (contact) Scheinost, Dustin Yale University 2017 Active
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A thorough understanding of brain function requires the integration of neuroscience data across species and scales. While current software can verify data quality within one or a handful of data sources, reproducibility across multiple data sources is limited. Xenophon Papademetris and colleagues are developing software tools with cross-scale, cross-species reproducibility analysis in mind. By leveraging data created by two other BRAIN Initiative projects at Yale University, Papademetris will extend current software algorithms to incorporate data from multiple sources, design the software to be cross-platform compatible, validate the software through rigorous testing, and finally, distribute it to the community. The potential for a set of software tools to reliably and reproducibly analyze multiple heterogeneous neuroscience data types will help to break down data barriers for the greater neuroscience community.

Multi-region 'Network of Networks' Recurrent Neural Network Models of Adaptive and Maladaptive Learning Rajan, Kanaka Icahn School Of Medicine At Mount Sinai 2019 Active
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Transformative new technologies can now capture neural activity from thousands of single neurons at high resolution. However, they produce large-scale datasets whose analysis and interpretation represent a bottleneck for computational models and theories, which must account for brain areas as interacting, intercommunicating neural circuits. For this project, Dr. Kanaka Rajan and her team will develop powerful, scalable, multi-region, neural network models and analysis tools for addressing this bottleneck.  The group will model the computations occurring across multiple brain regions during complex behavior, first using zebrafish as a test case before scaling up and expanding the range of their models. Success of this project will open up new avenues for probing circuit mechanisms within and between brain regions in both health and disease.

Multi-regional neural circuit dynamics underlying short-term memory Druckmann, Shaul Li, Nuo (contact) Baylor College Of Medicine 2017 Active
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Short-term memory is involved in many core cognitive behaviors, but it remains unclear whether its neural circuitry is mediated by a single distributed circuit or by many distinct parallel representations, and whether causal relations exist between regions. Nuo Lui and Shaul Druckmann are using optogenetic approaches to selectively perturb brain regions, observing whether this disruption in persistent activity in mouse frontal cortex also results in transient and/or lasting disruptions in behavior. By developing new analysis and modeling techniques to convert neural recordings and perturbations into circuit models, this work could provide a comprehensive investigation of the multi-region circuits that mediate short-term memory.
Multi-regional neural circuit dynamics underlying short-term memory Druckmann, Shaul Li, Nuo (contact) Baylor College Of Medicine 2019 Active
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Short term memory (STM) is essential for reasoning, decision-making, and flexible behavior, yet the neural substrate for STM is poorly understood. This project will use advanced techniques to first map and record circuits involved in STM and then use that information to selectively perturb individual circuits during specific tasks to better understand how these circuits and brain-wide activity dynamics generate memory-supported behaviors.

Multilevel Analysis of Neuronal Computations Underlying the Robust Encoding of Sensory Information in the Mammalian Olfactory System Arenkiel, Benjamin R Pfaffinger, Paul (contact) Baylor College Of Medicine 2019 Active
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In many ways, the brain is a computer, performing complex calculations that result in behavior, but those exact mechanisms are unknown. Dr. Pfaffinger’s team will use live imaging, electrophysiology, computational modeling, and genetic approaches to comprehensively look at the olfactory system, including its circuitry, how the brain responds to odors, and how that changes during learning. These studies will help inform general circuitry principles as well as how the brain processes sensory information. 

Multimodal modeling framework for fusing structural and functional connectome data Nagarajan, Srikantan S. Raj, Ashish (contact) Weill Medical Coll Of Cornell Univ 2016 Active
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Recent advances in the development of imaging tools are allowing researchers to both measure brain function (i.e., EEG, fMRI, PET) and the underlying structure of brain connections (i.e., diffusion MRI). Integrating functional brain activity data across imaging platforms, each of which provide unique information, has been tricky, as has been combining that data with structural connectivity data. Raj and his team are developing sophisticated modeling programs that combine this wealth of data across multiple spatial scales. These programs will provide insight into the relationship between brain function and structure and how the relationship is altered in cases of injury and disease.
Multiplex imaging of neuronal activity and signaling dynamics underlying learning in discrete amygdala circuits of behaving mice. Li, Bo Mao, Tianyi Zhong, Haining (contact) Oregon Health & Science University 2018 Active
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Dysfunction in the amygdala circuitry has large ramifications for myriad actions including those driven by threat or reward, and is essential for both learned behaviors - and for mood. How individual learning tasks differentially change this circuit to produce different behaviors remains largely unknown. Haining Zhong’s team will perform two-photon, multiplex imaging using a tiny GRIN lens, which allows optical access to deep brain structures, to image calcium activity as a proxy for neuronal firing in the amygdalae of behaving mice. Simultaneously, they will image the activity dynamics of the biochemical cAMP/PKA signaling pathway, as a readout for stress-/reward-induced neuromodulation. The team aims to discover and characterize, with cell-type specificity, functional subdivisions of the amygdala. This work may improve understanding of neuropsychiatric diseases associated with amygdala dysfunction.
Multiscale analysis of how the basal ganglia impact cortical processing in behaving mice Jaeger, Dieter Emory University 2019 Active
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Questions remain as to how output from the basal ganglia affects cerebral cortical activity during the processes of decision making, motor planning, and movement. Using modern molecular, imaging, and behavior approaches, this project will address questions of how basal ganglia output leads to cortical activation at the level of individual neurons and networks. Based on the information gathered, the researchers will build a thalamo-cortical network model to test which basal ganglia outputs and stimulus patterns are responsible for specific behaviors.

MULTISCALE ANALYSIS OF SENSORY-MOTOR CORTICAL GATING IN BEHAVING MICE Jaeger, Dieter (contact) Stanley, Garrett B. Emory University 2015 Complete
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The neural circuitry underlying how animals make motor decisions, especially in response to sensory or environmental cues, is not well understood. Many motor disorders, including Parkinson’s and Huntington’s disease, are linked to faulty circuits in a region of the brain called the basal ganglia. Researchers will use a variety of advanced methods to image, record, and manipulate the activity of neurons in this area as well as in the areas of the brain involved in sensory perception and movement. By employing these methods at multiple scales – from the individual neuron to neuronal networks – and then correlating these data with the behavior of awake, behaving mice, researchers hope to reveal how sensory information is integrated with input from the basal ganglia to result in the decision to initiate or suppress movement.
Multiscale Imaging of Spontaneous Activity in Cortex: Mechanisms, Development and Function Constable, R. Todd Crair, Michael (contact) Yale University 2015 Complete
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Being able to observe the activity of a single neuron while simultaneously observing the activity of entire brain regions is a critical step in bridging the gap in understanding of how a collection of nerve cells ultimately generates an organized behavior. Dr. Crair and colleagues will develop and use two different imaging techniques to measure the activity of individual neurons, regions of the brain, and the whole brain, during different behavior states, such as REM and non-REM sleep, in developing mice. Bridging their analyses and insights between and within scales will allow these researchers to examine neural circuits and networks in different brain states and determine how they are modulated through development.
Network basis of action selection Komiyama, Takaki Kreitzer, Anatol (contact) Lim, Byungkook J. David Gladstone Institutes 2015 Complete
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Three separate research groups are collaborating to understand in detail how three distinct areas of the brain function and work together to enable learning and decision-making behaviors. Drs. Kreitzer, Komiyama, and Lim are leveraging an impressive set of technologies to monitor and perturb different cell types in each brain region while the mice perform learning and decision-making tasks. By applying multiple recording methods across these brain regions at both the level of a single neuron and entire subpopulations of neurons, while the animals perform the same set of tasks, researchers hope to develop a single model of how vertebrate animals make choices about what to do next.

Network Connectivity Modeling of Heterogeneous Brain Data to Examine Ensembles of Activity Across Two Levels of Dimensionality Gates, Kathleen Univ Of North Carolina Chapel Hill 2016 Active
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Functional MRI (fMRI) is currently the most ubiquitous imaging technique for measuring whole brain activity in humans. The usefulness of fMRI in both research and clinical settings, however, has been limited by the availability of computational tools for analyzing the data. Most tools allow researchers to track activity in brain regions within a known network, without the ability to simultaneously examine connections between various networks. Gates and her colleagues have proposed a set of software tools that enable the simultaneous analysis of within- and between-network connectivity. The tools will also make it easier to combine fMRI data across individuals in order to learn more about how whole brain activity differs across people in both health and disease.
Neural circuits for spatial navigation Maimon, Gaby Rockefeller University 2018 Active
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A circuit-level understanding of how brains perform quantitative, navigation-related computations would be a major advance for neuroscience. Gaby Maimon’s team will study how brains construct navigational signals and how these signals guide behavior. Using physiological recordings in active fruit flies, they seek to identify a circuit by which sensory information arrives at the central brain (where neurons respond to sensory-motor signals) to update the head-direction when flies turn in darkness. To investigate whether the fly’s internal heading/compass signal is needed for them to keep a straight bearing, the researchers will take recordings after impairing this system. Finally, they will test whether flies have forward speed-sensitive neurons that enable 2D navigation. Such discoveries could elucidate how model brain machinery can perform day-to-day navigation tasks, and how to approach conditions in which these abilities are impaired, such as Alzheimer’s disease.
Neural circuits in zebrafish: form, function and plasticity Cepko, Constance L Engert, Florian (contact) Lichtman, Jeff W Sompolinsky, Haim Harvard University 2014 Complete
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Dr. Engert's team will combine a wide array of cutting-edge neuroscience techniques to watch the entire brain activity of a see-through fish while it swims, and to make detailed maps of its brain circuitry.
Neural circuits underlying thirst and satiety regulation Oka, Yuki CALIFORNIA INSTITUTE OF TECHNOLOGY 2018 Active
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The neural circuits involved in the regulation of thirst and satiety remain poorly understood. Classical models postulate that water deficits drive appetite, which is sated when the internal environment is rehydrated. Using viral tracing studies, in vivo optical recording in mice, retrograde labeling, and single-cell RNA-seq analysis, Dr. Oka and team will test the hypothesis that ingestive behavior itself directly modulates appetite in the brain before the body is satiated. This work will bring new understanding to the role of thirst circuits and drinking behavior.

Neural Computation for Innate Behaviors in the Superior Colliculus Meister, Markus California Institute Of Technology 2019 Active
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The brain receives a significant amount of sensory data all the time but is able to filter data to make informed decisions. Dr. Meister and colleagues are studying an area of the brain, the superior colliculus (SC), that links visual input from the eye to motor decisions. Using a previously developed computational model for SC processing, Dr. Meister’s team aims to understand the anatomy of the SC; determine how the SC processes specific visual inputs; and determine the role the SC plays in visual memory.

Neural Computations Underlying Vocal Sensorimotor Transformations Long, Michael A New York University School Of Medicine 2019 Active
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This project aims to investigate the circuit mechanisms that underlie sensorimotor transformations. Using behavioral, molecular, and electrophysiological approaches, this project will characterize the neural basis of rapid vocal exchanges using the singing mouse as a model system that engages in “countersinging,” a socially modulated behavior. 

Neural ensembles underlying natural tracking behavior Fiete, Ila R. Huk, Alexander C Priebe, Nicholas J. (contact) University Of Texas, Austin 2015 Complete
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Animals move their eyes to track the movement of objects around them. These researchers will measure and manipulate the activity of populations of identified neurons in marmosets during pursuit eye movements. This work will allow a detailed understanding of how the pursuit circuit integrates information from a large number regions is a critical step in bridging the gap in understanding of how a collection of nerve cells ultimately generates an organized behavior. Dr. Crair and colleagues will develop and use two different imaging techniques to measure the activity of individual neurons, regions of the brain, and the whole brain, during different behavior states, such as REM and non-REM sleep, in developing mice. Bridging their analyses and insights between and within scales will allow these researchers to examine neural circuits and networks in different brain states and determine how they are modulated through development.
Neural mechanisms and behavioral consequences of non-Gaussian likelihoods in sensorimotor learning Nemenman, Ilya M. (contact) Sober, Samuel Emory University 2016 Active
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A central goal of neuroscience is to understand how learning is implemented by the nervous system. However, despite years of studies in animals and humans, our knowledge of both the computational basis of learning and its implementation by the brain is still rudimentary. This project by Nemenman and his colleagues will spawn a unified mathematical theory explaining how the brain learns complex skills. The researchers will validate their theory in songbirds, with the goal of understanding sensorimotor learning of a single acoustic parameter, pitch, which is precisely regulated by the songbird brain. A better understanding of the mechanisms underlying sensorimotor learning could guide rehabilitative strategies that exploit the plasticity of complex behavior.
Neural mechanisms of active avoidance behavior Castro-alamancos, Manuel A Drexel University 2018 Active
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Maladaptive, active avoidance behavior is present in most forms of pathological anxiety. To better understand this process, Castro-Alamancos and colleagues will study freely-behaving, genetically-modified mice performing active avoidance (e.g., withdrawing from aversive noise or mild electrical foot shocks). They will employ behavioral, electrophysiological, optogenetic, chemogenetic, pharmacological, and histological procedures to test some of specific hypotheses: 1) The substantia nigra pars reticulata (SNr) mediates active avoidance behavior via projections to midbrain locomotor regions. and 2) Specific regions of the striatum control SNr activity during avoidance via connections projecting from the striatum to the substantia nigra. This project will provide understanding about the neural circuits responsible for active avoidance behavior.
Neural representation of mating partners by male C. elegans Linderman, Scott Warren Samuel, Aravinthan D. Sternberg, Paul Warren (contact) California Institute Of Technology 2019 Active
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Understanding the function of neural circuits requires knowledge about neural connectivity and activity in response to stimuli. Dr. Sternberg and colleagues aim to elucidate the full set of sensorimotor events that organize the mating behavior in C. elegans, taking advantage of its complete connectome along with computational modeling and cell-specific manipulations. They will catalog the sensorimotor events that organize mating behavior; model the circuits involved in the mating process; and use genetic tools to characterize each type of sensory neuron involved. This research may give insight into precise circuit control of a specific behavior – the type of understanding that helps neuroscientists better understand how the brain works.

Neural sequences for planning and production of learned vocalizations Cooper, Brenton G. Hahnloser, Richard Roberts, Todd F (contact) Ut Southwestern Medical Center 2018 Active
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To understand how the brain controls voluntary movements via sequences of neuronal activity, Dr. Roberts and colleagues intend to study how the brains of songbirds control singing, a natural behavior. For this project they will use calcium imaging, electrophysiological recordings, and optogenetic manipulations in a cell-type specific manner to investigate how specific circuits help songbirds plan, prepare, and sing their songs. The work could improve our understanding of how patterns of neuronal activity integrate to allow voluntary, skilled actions, which may help researchers understand how the breakdown of these circuits can cause movement disorders, like Parkinson’s disease.

Neural signatures of learning complex environments in the amygdala-prefrontal network Barack, David Columbia University Health Sciences 2019 Active
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The ability to learn, think, and make decisions in complex environments is extremely important to critical life functions across species, but the neural correlates of external and internal representative states are largely unstudied. Recent studies suggest activity in the amygdala and orbitofrontal cortex correlate to state representation, but their exact roles are unknown. Dr. Barack aims to investigate how monkeys learn these state representations, using a complex, sequential decision-making task. During this novel behavioral task, similar to the boardgame “Battleship,” the team with elucidate learning in a complex environment, measuring associated neural mechanisms of circuits in the amygdala and orbitofrontal cortex activated in learning and decision-making. These results could promote the creation of computational models that may provide insights about animal and human interactions with the world.

Neuroethics of aDBS Systems Targeting Neuropsychiatric and Movement Disorders Goodman, Wayne K Lazaro-munoz, Gabriel (contact) Mcguire, Amy Lynn Baylor College Of Medicine 2017 Active
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A technological advance beyond traditional, open-loop DBS devices, adaptive deep brain stimulation (aDBS) devices monitor local neural activity to adjust stimulation in real time when treating certain movement and neuropsychiatric disorders. However, because aDBS devices autonomously record neural data and provide neuromodulation to affect motor function and mood, these systems raise important neuroethics issues, including changes in perception of autonomy and personal identity; risk-taking propensity; and privacy, use, and ownership of neural data. In this project, Dr. Lazaro-Munoz and colleagues will gather data from participants in existing aDBS clinical trials, their caregivers, people who declined to receive aDBS, and the aDBS researchers, to identify and assess the most pressing neuroethics issues related to aDBS research and translation. The long-term goal of this research program is to develop an empirically-informed and ethically-justified framework for the responsible development and clinical translation of aDBS systems, which will help maximize the social utility of this type of novel neurotechnology.
Neuromodulation approaches for restoring dexterous control following cortical stroke. Khanna, Preeya University Of California, San Francisco 2019 Active
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Despite physical therapy, about 50% of stroke survivors must live with impaired hand function, impacting daily activities for the remainder of their life. However, recent studies in rats have suggested that low-frequency cortical stimulation may help alleviate such symptoms. In order to translate this work to humans, Dr. Khanna aims to use a multiscale model of electrophysiological recording to monitor motor and somatosensory activity during dexterous control, comparing affected and unaffected hemispheres in non-human primates (NHP) recovering from a stroke. The results may inform development of therapeutic techniques for stroke-related motor dysfunction, while improving our understanding of neuromodulation.

Neuromodulation of Brain States Luo, Liqun Stanford University 2018 Active
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Abnormalities of the serotonin neuromodulatory system contribute to mood disorders. In rodents, Luo’s team will use their recently-developed viral-genetic tools to dissect the complexities of the serotonin system into specific sub-systems. They will anatomically characterize the organization of the dorsal raphe (DR)-serotonin sub-systems, identifying how each sub-system divides up the projections of the entire DR-serotonin system, as well as the input-output relationship for each sub-system. Sub-system behavioral functions will be determined by manipulating and recording serotonin neuron subtypes in anxiety- and depression-like states. Finally, the team will explore the circuit and cellular mechanisms by which serotonin regulates thirst-motivated behavior, using a technique to genetically manipulate thirst-activated neurons. This work could elucidate how serotonin modulates diverse physiological functions and behaviors.
Neuromodulatory control of collective circuit dynamics in C. elegans Flavell, Steven Willem Massachusetts Institute Of Technology 2017 Active
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The neural mechanisms that allow animals to initiate, maintain, and terminate long-lasting behavioral states (e.g., sleep/wake, emotional, and cognitive states) are unknown. Steven Flavell’s team aims to identify, in freely-moving C. elegans, the circuit-wide neural dynamics that define roaming and dwelling behavioral states, and to examine how specific neuromodulators coordinate the activity of their target neurons to organize whole-circuit activity patterns over long stretches of time. The team will combine their own newly-developed calcium imaging technology, which can simultaneously monitor every neuron in a circuit, with genetic/optogenetic manipulations (e.g., neuromodulator deletions and inter-neuron functional connectivity perturbations) and with novel analysis/modeling methods. These studies could help reveal how neuromodulators orchestrate whole-circuit changes in activity to influence animal behavior.
Neuronal and Dopaminergic Contributions to Dissimilar Evoked Hemodynamic Responses in the Striatum Walton, Lindsay Univ Of North Carolina Chapel Hill 2018 Active
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Blood oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) is a non-invasive imaging technique that infers increased brain activity from observed increases in cerebral blood flow. A notable exception to this relationship occurs in the striatum. Walton will investigate the activity of dopamine neurons, medium spiny neurons, and dopamine receptors, under conditions that evoke either blood vessel dilatation or constriction in the striatum. She will utilize optogenetic stimulation, synthetically-derived receptors, and receptor antagonist drugs to reveal the mechanisms underlying striatal positive and negative fMRI responses. These studies are important for the accurate interpretation of BOLD fMRI signals from brain regions with atypical hemodynamic responses.
Neuronal circuits for context-driven bias in auditory categorization Cohen, Yale E Geffen, Maria Neimark (contact) Kording, Konrad P. University Of Pennsylvania 2019 Active
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The sensory signals and our brain’s response to them is noisy, which means that we must perform important cognitive tasks based on uncertain information. Dr. Geffen and colleagues aim to generate a computational framework and identify the circuits involved in one type of these cognitive tasks, auditory characterization. Using mice trained in forced choice tasks prompted by auditory stimuli, they will gather data from the auditory and posterior parietal cortices to gain insights that can be applied to hearing dysfunction, perception, and cognition. These findings will be important in developing clinical approaches to alleviating hearing difficulties in complex acoustic environments as well as potentially helping patients with deficits in cognitive tasks such as those with schizophrenia or other psychiatric disorders.

Neuronal mechanisms of human episodic memory Mamelak, Adam Nathaniel Rutishauser, Ueli (contact) Cedars-sinai Medical Center 2017 Active
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No meaningful therapies for memory disorders exist, partially due to a lack of mechanistic knowledge about human memory. Ueli Rutishauser’s multi-institutional, multi-disciplinary team will study how memories of facts and events are formed and used in the human brain. The team will use electrophysiological methods to record single neurons, simultaneously in multiple brain areas, in awake patients who are implanted with electrodes to localize epileptic seizures. This work will combine single-neuron physiology, behavioral testing, electrical stimulation, and computational modeling, to address three questions: (i) how persistent activity supports memory formation, (ii) what mechanisms translate memories into decisions and judgments, and (iii) how memories are formed and recalled over time. A circuit-level understanding of memory may enable development of new treatments for memory disorders.
Neuronal population dynamics within and across cortical areas Doiron, Brent UNIVERSITY OF PITTSBURGH AT PITTSBURGH 2018 Active
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Drs. Doiron, Smith, and Yu will develop a method that combines large-scale network modeling, large-scale neural recordings, and neural population analyses to understand the key network principles that drive behavior. The team proposes to validate their methods using data recorded from macaque prefrontal cortex to the visual area, V4. A toolkit called Balance BEAM (Brains, Experiments, Analysis and Models), implemented in Matlab, will include a graphical user interface for designing balanced, optimized network models. If successful, Balance BEAM will allow future users to better research how neural circuits give rise to transient activity, steady-state activity, and neural variability.

Neuronal Substrates of Hemodynamic Signals in the Prefrontal Cortex Howard, Matthew A. O'doherty, John P (contact) Tsao, Doris Ying California Institute Of Technology 2016 Active
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Functional MRI (fMRI) is the dominant technique for probing human prefrontal cortex functions such as cognition, learning, and decision-making. Yet, little is known about how fMRI signals relate to the underlying neural signals in prefrontal cortex. O’Doherty and his colleagues will examine this relationship in monkeys by first probing the region with fMRI, then recording electrical signals from individual neurons in those areas that show strong fMRI activation. The team will then follow up with dual recordings (fMRI and intracranial electrical measurements) in human patients undergoing surgical treatment for epilepsy. By combining these different recording techniques in both monkeys and humans, the team hopes to determine which aspects of underlying neural responses give rise to fMRI responses in prefrontal cortex. This work will improve the usefulness of fMRI as a diagnostic measure of disorders related to higher-order cognitive functions.
Neurons, Vessels and Voxels: Multi-modal Imaging of Layer Specific Signals Kara, Prakash Naselaris, Thomas P Olman, Cheryl A. Ugurbil, Kamil (contact) University Of Minnesota 2016 Active
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Functional MRI (fMRI) infers the location and magnitude of neural activity from vascular signals. However, the technique has not been shown to distinguish neural activity from individual cortical layers, each of which have unique computational functions. To demonstrate ultrahigh-resolution high-field fMRI’s ability to measure layer-specific signals, Ugurbil and his colleagues will perform simultaneous 2-photon microscopy—a technique for imaging neural signals with high spatial resolution—and fMRI experiments in which cats are shown visual stimuli known to elicit responses in specific cortical layers. These experiments will seek to correlate layer-specific fMRI responses with differences in neural activity, which will ultimately enable fMRI to provide more detailed information about human brain function in both health and disease.
Neurostimulation and Recording of Real World Spatial Navigation in Humans Suthana, Nanthia A University Of California Los Angeles 2017 Active
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Spatial memory is thought to involve neurons in the medial temporal lobe that exhibit increased firing rates when an animal is in a specific location during spatial navigation. However, human single-neuron studies have been limited to immobile subjects viewing 2-dimensional navigational tasks. Nanthia Suthana’s team will use intracranial single-neuron and local field potential recordings, combined with deep brain stimulation (DBS), in epilepsy patients performing freely-moving spatial navigation memory tasks using state-of-the-art virtual reality headset technology and full-body motion capture. The team will record from medial temporal lobe subregions, to determine the role of single neurons and oscillations during navigation and memory, and how these neurophysiological mechanisms can be enhanced by deep brain stimulation. This work may yield insights into the neuronal correlates of real-world spatial navigation and memory.
New methods and theories to interrogate organizational principles from single cell to neuronal networks Dierssen, Mara Ye, Bing (contact) University Of Michigan At Ann Arbor 2019 Active
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Understanding how individual neurons contribute to network functions is fundamental to neuroscience, but the link between neuronal structure and network connectivity is unclear. Dr. Bing Ye and his team will develop and validate a user-friendly toolset for discovering the rules that link neuronal morphology to network connectivity, allowing them to make predictions about neural network properties based on the structure of single neurons. This open-source computational tool will incorporate visualization and analysis of neuronal populations derived from imaging data, as well as models for interrogating the organizational principles underlying brain network architecture. The successful development of these novel computational tools will enable researchers to investigate how the shapes of individual cells contribute to the connectivity of the nervous system in both health and disease.

Next-Generation Calcium Imaging Analysis Methods Paninski, Liam M Columbia Univ New York Morningside 2016 Active
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Tracking the flow of calcium ions into and out of neurons is a good way to monitor the simultaneous activity of many neurons with single-cell resolution. The proliferation of high-resolution, high-throughput calcium imaging equipment is generating enormous 2D and 3D datasets that are challenging to interpret. Paninski and his colleagues are working on innovative statistical and computational approaches to make sense of those imaging data and to combine them with other types of data, such as those from multielectrode arrays. The proposed analytical methods will be scalable, modular, and extensible, providing flexibility to users and developers.
Next-generation high-resolution diffusion MRI resolving cortical columns and layers in vivo Song, Allen W (contact) Truong, Trong-kha Duke University 2019 Active
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Development of next generation non-invasive imaging techniques could help clinicians identify neuronal markers of neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease. Drs. Song, Truong, and colleagues will develop ultrahigh resolution (sub-millimeter) diffusion MRI acquisition methodologies to map white and gray matter neuronal cortical tracts, columns, and layers in the human brain. They will create a new 48-channel iPRES (integrated parallel reception, excitation, and shimming) AIRcoil array (a new generation of radiofrequency coils based on GE Healthcare’s AIR TechnologyTM), integrated with 3 Tesla magnetic field strength, to allow for deep brain penetration with high spatial fidelity. This novel technology will be able to detect subtle, microstructural changes in very early stage neurodegenerative diseases, when interventions can be most effective.

Next-generation optical brain functional imaging platform Fang, Qianqian Northeastern University 2018 Active
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Non-invasive imaging techniques are restricted by their lack of portability, which leads to limited, lab-based experiments. Advancing neuroscience research requires improvements in emerging optical methods, such as functional near-infrared spectroscopy (fNIRS), to continually assess brain dynamics in natural environments. Dr. Qianqian Fang and a team of investigators will design wearable optical imaging headgear and develop an imaging analysis pipeline that improves image resolution and contrast. Through validation of their platform in a small-scale clinical study, the group will create an advanced optical brain imaging platform that is wireless and compact. This proposed work has the potential to reduce cost and weight of optical imaging systems, while providing improved image resolution and accuracy, paving the way for optical methods as an important monitoring tool.

Nonlinear Causal Analysis of Neural Signals Sejnowski, Terrence J University Of California, San Diego 2018 Active
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Understanding how neural signals from different parts of the brain impact each other over time could help reveal differences in information flow during typical and abnormal cortical states. Dr. Sejnowski proposes to develop a new algorithm for the causal analysis of time-series data called cross-dynamical Delay Differential Analysis (CD-DDA), for modeling time- series data. The work should extend CD-DDA to identify causally- connected brain network phenomena, using simulated Hodgkin-Huxley network models and electrocorticography recordings from epilepsy patients. Though this project uses electrocorticography data to validate CD- DDA, the tool can be applied to calcium recordings from single neurons, voltage sensitive dye recordings, local field potentials, EEG, MEG, and fMRI data. These analytical methods could help future users uncover the influence of information flow across cortical areas on activity of different neuronal populations.

Norepinephrine modulation of neocortex during flexible behavior Cohen, Jeremiah Yaacov (contact) O'connor, Daniel Hans Johns Hopkins University 2018 Active
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Flexible behavior requires that animals explore their environment and respond to changes, while exploiting features of the environment that have known value. Cohen and colleagues will test a theory that the neurotransmitter norepinephrine facilitates behavioral flexibility by modulating neocortical activity. During reward-based behavioral tasks, the team will record and manipulate the activity of norepinephrine-releasing neurons in the locus coeruleus (the primary source of forebrain norepinephrine), as well as their targets in the sensory and prefrontal cortex of mice. Understanding how norepinephrine modulates the neocortex in the context of behavior will be necessary to understand disorders of attention and mood that rely on norepinephrine signaling.
Novel Bayesian linear dynamical systems-based methods for discovering human brain circuit dynamics in health and disease Menon, Vinod Stanford University 2016 Active
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It is currently not known how dynamic patterns of brain activity are transformed into cognition, emotion, perception and action in both health and disease in humans. Menon and his colleagues plan to develop novel algorithms for identifying dynamic functional networks in the brain and characterizing network interactions between brain regions involved in cognitive tasks, translating their studies from in vivo rodent data to humans. The researchers’ algorithms will facilitate rigorous investigations of brain dynamics that support critical cognitive functions and significantly advance the understanding of dynamic processes underlying human brain function and dysfunction. As an example, one of the major goals of the project will be using the newly created algorithms to investigate aberrant functional circuits associated with cognitive impairments in Parkinson’s disease.

NWB:N: A Data Standard and Software Ecosystem for Neurophysiology Ng, Lydia Lup-ming Ruebel, Oliver (contact) University Of Calif-lawrenc Berkeley Lab 2018 Active
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Neurophysiology research, which focuses on recording brain cell activity, produces enormous amounts of complex data that are difficult to manage. Drs. Rubel and Ng will build upon the Neurodata Without Borders: Neurophysiology project to create a system that will allow for standardizing, sharing, and reusing neurophysiological data. The team will design an open source software system; develop methods to establish a consistent vocabulary for defining cell types, measurements, and behavioral tasks; and create tools to help the community adopt these new resources and standards. The proposed system will help accelerate neurophysiological discoveries as well as reproducibility studies.

OpenNeuro: An open archive for analysis and sharing of BRAIN Initiative data Poldrack, Russell A Stanford University 2018 Active
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To leverage the public investment in the BRAIN Initiative, the sharing of data produced by its myriad projects is paramount. Dr. Podrack’s project extends the recently released OpenNeuro, which was developed based on the well-established and successful OpenfMRI, for an archive of neuroimaging data. The extended archive encompasses a broader range of neuroimaging data including EEG, MEG, diffusion MRI and others. The archive also implements easy-to-use data submission, semi-automated curation and advanced data processing workflows, which run directly on the cloud platform. The archive allows to share the results alongside the data, federate with other relevant repositories, and accessible to all researchers.

Optimization and distribution of high density cellular scale carbon and silicon arrays Chestek, Cynthia UNIVERSITY OF MICHIGAN AT ANN ARBOR 2018 Active
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Much of our understanding of how the brain functions has come from recordings made via electrodes placed deep within the brain. However, metal electrodes can cause damage to the brain, making simultaneous visual analysis challenging. New carbon fiber electrodes developed by Dr. Chestek and her group will be much thinner and cause significantly less damage than traditional methods. Further, these new fibers can be left inside the brain tissue long-term and remain in place for analysis of placement after tissue dissection. These advances, tested in mice, will allow researchers to record from large numbers of neurons at the same time without damaging them and will help advance our understanding of how neurons communicate with each other.

Oxytocin Modulation of Neural Circuit Function and Behavior Tsien, Richard W New York University School Of Medicine 2018 Active
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While oxytocin hormonal signaling has been studied in maternal behavior and implicated in several brain disorders, we know little about how variations in its release modulates the circuits that regulate social behaviors. Tsien’s group will develop new tools and cutting-edge techniques with large-scale methods to tackle the oxytocin system from both the source (oxytocin neurons) and the receiving ends (oxytocin receptor-expressing neurons). From the source, they will address the connectivity, behavioral influence, in vivo responses, release, and experience-dependent changes of the oxytocin neurons. From the receiving ends, they will dive into detailed cellular, synaptic, and microcircuit mechanisms that mediate oxytocin actions. With these data, they plan to explore state-dependent changes in aggression due to oxytocin. A better understanding of the endogenous action of oxytocin is key to unleashing its therapeutic potential.

Pediatric Deep Brain Stimulation: Neuroethics and Decision Making Blumenthal-barby, Jennifer Lazaro-munoz, Gabriel (contact) Storch, Eric A. Baylor College Of Medicine 2019 Active
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Deep brain stimulation (DBS) is currently used in children with dystonia, epilepsy, and Tourette Syndrome, and this use is expanding to other neuropsychiatric conditions. In doing so, there are several challenging ethical issues, and no consistent guidance on the use of DBS in pediatric populations. To address this challenge, Dr. Gabriel Lazaro-Munoz and team will examine neuroethics issues and decisional and informational needs of families by conducting interviews with pDBS stakeholders (minors, caregivers, and clinicians). These interviews will inform the development of a decision aid for caregivers considering DBS for dystonia, the most common use of pDBS. This project will provide key information about the ethical issues facing families, minors, and clinicians alike when considering pDBS, as well as develop a clinical decision aid for making informed, patient-centered decisions surrounding the clinical use of invasive neuromodulation in minors.

Population Neural Activity Mediating Sensory Perception Across Modalities CLANDININ, THOMAS ROBERT et al. STANFORD UNIVERSITY 2018 Active
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Understanding how the brain processes sensory information to result in selected behaviors remains a challenge in the field of neuroscience. Drs. Clandinin, Ganguli, Murthy, and Scott will utilize the fruit fly model to examine how different sensory pathways and timescales interact at the brain-wide level. Their project will involve synthetic and naturalistic sensory stimuli of three modalities (vision, taste, and mechanosensation) alongside state-of-the-art in vivo two-photon calcium imaging. By incorporating brain-wide results across sensory modalities in Drosophila, along with circuit algorithms and cell-type specific aspects of sensory integration these studies can help inform neural circuit function of sensory processing in more complex systems. 

Predictive models of brain dynamics during decision making and their validation using distributed optogenetic stimulation Pesaran, Bijan New York University 2017 Active
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Distributed across the frontal and parietal cortices are circuits through which our brains combine sensory information and experience to select spatial goals for movement. Different areas in the frontal-parietal circuit have specialized functional roles, but the neural activity patterns within those areas remain unclear. Bijan Pesaran’s team will develop and validate predictive models of neuronal dynamics underlying visual-saccadic decision-making. They will use electrophysiology and optogenetic stimulation in non-human primates performing a decision task. While monitoring activity and behavior, the team will assign functional roles to neural activity patterns by precisely perturbing the circuit (via temporally-patterned optogenetic stimulation) to achieve targeted neural activity states predicted by the numerical model. This project’s success may offer new ways to delineate the contributions of different cortical areas to attentional selection and decision-making.
Proprioceptive Coding of Jaw Movement during Orofacial Behavior Olson, William Paul Johns Hopkins University 2019 Active
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Many orofacial behaviors critical for survival, such as chewing, drinking, and breathing, require motor command modulation based on information from proprioceptors. However, since many previous studies of proprioceptors were not performed in awake, behaving animals, our understanding of this system is lacking. Dr. Olson aims to target and record from mouse jaw-innervating proprioceptors in the mensencephalic trigeminal (MeV) nucleus, while the animals perform orofacial behaviors. Using advancements in in vivo physiology, behavioral analysis, and computational techniques, the study will entail recording from these neurons and mapping the functional organization of the area. The findings may improve our understanding of how the brain controls jaw movements in real-time.

Quantifying causality for neuroscience Kording, Konrad P. University Of Pennsylvania 2019 Active
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Understanding causality is central to neuroscience, both in how the action of one neuron affects another, as well as in medical approaches that aim to produce causal effects. For this project, Dr. Konrad Kording and his team will develop a set of computational techniques that will allow neuroscientists to quantify how neurons causally influence one another. To do so, they will utilize approaches popular in econometrics, wherein the observation of variables that approximate random system perturbations will allow for the discovery of causal relations. The interdisciplinary team will apply these techniques to problems in neuroscience through a combination of machine learning and engineering, paving the way for important advances toward understanding and quantifying causality in both basic and clinical applications.

RAVE: A New Open Software Tool for Analysis and Visualization of Electrocorticography Data Beauchamp, Michael S Baylor College Of Medicine 2018 Active
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Electrocorticography (ECOG) allows the direct recording of a small population of neurons in human subjects, generating vast amounts of data. Dr. Beauchamp plans to develop the software RAVE (R Analysis and Visualization of Electrocorticography data) to help researchers explore such datasets. Incorporating established and successful informatics approaches that enable standardization, sharing, and re-use of neurophysiology data and analyses, RAVE includes rigorous statistical methodologies and seamless integration with existing analysis platforms. To facilitate user adoption and maximize impact, the developers plan to release RAVE 1.0 to the entire ECOG community within 6 months of the project start.

Readout and control of spatiotemporal neuronal codes for behavior Babadi, Behtash Chialvo, Dante R Fellin, Tommaso Histed, Mark H Kanold, Patrick O Losert, Wolfgang Maunsell, John Hr (contact) Panzeri, Stefano Vt Plenz, Dietmar Rinberg, Dmitry Shoham, Shy University Of Chicago 2018 Active
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Organisms must accurately represent stimuli in the outside world and use that representation to generate behavioral actions. While it is understood that neuronal population responses carry information about specific external stimuli, it is unclear whether the brain “reads” this information to form sensory perceptions. Maunsell and colleagues have developed a patterned neuronal stimulation technology, previously funded via the BRAIN Initiative, and will apply it to answer long-standing questions about neural coding and readout in the visual, olfactory, and auditory systems. Using rodents, they will determine which neurons within a network are encoding behaviorally relevant information, and also determine the extent to which temporal patterns of those neurons’ activity are being used to guide behavior. A better understanding of neuronal mechanisms related to sensation and action will advance a theoretical framework for understanding neural codes, which could improve diagnosis for many neurological disorders.

Real-time statistical algorithms for controlling neural dynamics and behavior Park, Il Memming (contact) Pillow, Jonathan William State University New York Stony Brook 2018 Active
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High-throughput technologies help researchers understand how neural systems perform the computations that underlie perception, cognition, and behavior, but data obtained through simultaneous recordings from large groups of neurons and fine-grained behavioral tasks create a major bottleneck in data collection and analysis. Drs. Park and Pillow intend to develop statistical tools for tracking internal states of the brain that are not directly measurable from observation of behavior and neural signals. To uncover neuronal computations required for behavioral learning, the group will develop methods for tracking and enhancing the evolution of internal brain states during learning, generating optimal stimuli corresponding to those states to perturb or correct behavior. Subsequent evolution of this work could improve clinical tracking and intervention of neurological disorders with a behavioral component, like Parkinson’s disease. The effort will result in a real-time tool for tracking internal brain and behavioral states, applicable for both basic neuroscience research and clinical applications.

Recombinant Immunolabels for Nanoprecise Brain Mapping Across Scales Trimmer, James UNIVERSITY OF CALIFORNIA AT DAVIS 2018 Active
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Studying how the brain works from the molecular to the circuit level is crucial for improving our understanding of how the brain functions normally, and what goes wrong in various disorders. Antibody probe techniques are effective tools that work at both of those levels. This project will develop a collection of validated, recombinant antibodies that are also highly renewable. In addition, antibodies will be miniaturized to increase binding efficiency and improve labeling precision. These resources will provide a cutting-edge, validated set of research tools to enable neuroscience research across a variety of resolutions from the intracellular to the neuronal network level.

Relating functional MRI to neuronal activity: accounting for effects of microarchitecture Blazejewska, Anna I Massachusetts General Hospital 2019 Active
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fMRI can be a powerful tool to measure activity throughout the entire brain. But, because it is an indirect measure of activity through changes in blood oxygenation, it is subject to error based on local microstructural and microvascular properties of the cortex. Thus, Dr. Blazejewska intends to remove these biases in fMRI results, providing a framework for a more accurate representation of neural activity. Using histology of human brain specimens with advanced ex vivo and in vivo imaging, the team will map between tissue microarchitecture and fMRI results, correcting errors due to microstructure. These results should allow for a more accurate measurement of functional activity across all cortical layers, promoting a better understanding of the brain’s circuitry.

Repetitive transcranial ultrasound stimulation for modulating brain rhythms Dmochowski, Jacek City College Of New York 2018 Active
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Neural oscillations, which are temporal activity patterns in the brain, are recognized as fundamental to the brain’s information processing. Dmochowski and colleagues will evaluate the safety and efficacy of a new form of transcranial ultrasound stimulation (TUS), in which ultrasonic waves will modulate the activity of neural circuits with enhanced precision and specificity (on the order of millimeters). The team will determine whether TUS could be used to modify neural oscillations. This research may contribute foundational knowledge needed for development of new, non-surgical, ultrasonic treatments for disorders associated with abnormal brain rhythms, such as schizophrenia, Parkinson’s, and epilepsy.
Resource for Multiphoton Characterization of Genetically-Encoded Probes Drobizhev, Mikhail MONTANA STATE UNIVERSITY - BOZEMAN 2018 Active
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Two-photon microscopy has emerged as a key technique for studying the activity of living neural networks. However, little optimization has been performed for the associated fluorescent activity probes and sensors. Dr. Drobizhev’s research group will create a resource at Montana State University to characterize the properties of two-photon probes and make that service available to the broader research community. Given increased used of this type of resource by BRAIN Initiative investigators, the research group will also organize meetings to help other labs develop their own characterization processes.

Resting state connectivity: Biophysical basis for and improved fMRI measurements Kleinfeld, David (contact) Rosen, Bruce R University Of California San Diego 2016 Active
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Functional MRI (fMRI) is a unique tool that permits detailed measurements of neural activity within the entire volume of the human brain. A particularly powerful aspect of fMRI concerns measurements of coordinated fluctuations in the amplitude of blood oxygen level dependent (BOLD) signals across distant regions of the brain, referred to as “resting-state functional connections.” Kleinfeld and his colleagues plan to test the hypothesis that very subtle oscillations in the smooth muscle of arteriole walls in the brain links oscillations in with the resting-state BOLD signals. Being able to measuring resting-state connectivity by assessing arteriole movements can advance scientists’ use of fMRI to study human cognition as well as a variety of neuropsychiatric conditions.
Revealing neural computations through combined optical and electrical recordings Field, Gregory Darin (contact) Sher, Alexander Duke University 2019 Active
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The retina is a thin layer of eye tissue that turns what we see into signals that are sent to the brain. It remains a challenge to understand how information is processed across the multiple layers of the highly interconnected neurons in the retina. To address this, the Field and Sher groups will develop a technology that combines large-scale optical and electrical recordings and visual stimulation to determine how diverse cell types in the retina shape its function. The results may help researchers understand the circuit dynamics behind vision and blindness and provide clues to universal principles that govern how circuits throughout the nervous system process information.

Revealing the connectivity and functionality of brain stem circuits Berg, Darwin K Deschenes, Martin Freund, Yoav Shai Goulding, Martyn D Kleinfeld, David (contact) Knutsen, Per M University Of California San Diego 2014 Complete
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Dr. Kleinfeld and his colleagues will use a variety of tools and techniques to create detailed maps of circuits in the brainstem, the region that regulates many life-sustaining functions such as breathing and swallowing, and match the circuits to actions they control.
Revealing the transcriptional and developmental mechanisms of interneuron identity Crow, Megan Cold Spring Harbor Laboratory 2019 Active
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GABAergic interneurons have a key role in regulating circuits in the brain, and their dysfunction is linked to neurodevelopmental diseases. It is known that diversity exists between classes of interneurons, but the extent and mechanisms of this diversity are unknown. Dr. Crow will explore the transcriptional, epigenetic, and developmental mechanisms that govern interneuron diversity, in a cross-species analysis. The work will leverage computational and phylogenetic models, machine learning, and advances in single cell RNA-sequencing technology to shed light on interneuron identity.

Reverse Engineering the Brain Stem Circuits that Govern Exploratory Behavior Deschenes, Martin Freund, Yoav Shai Golomb, David Kleinfeld, David (contact) Mitra, Partha Pratim Wang, Fan University Of California, San Diego 2018 Active
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An overarching question in neuroscience is how motor actions are coordinated to form different behaviors. Orofacial motor actions in rodents (e.g., head bobbing, vibrissa whisking, and licking with the tongue) coordinate to simultaneously serve exploration without conflicting with life-supporting motor actions like breathing and swallowing. However, the neural basis for orofacial motor coordination remains elusive. Kleinfeld and colleagues aim to reverse engineer brainstem circuits that guide orofacial motor actions. The team will advance computational models and various neuroscience and machine learning tools to add informative labels to individual brainstem neurons, place these cells within circuits, connect circuits with motor actions, and coordinate different actions into behaviors. If successful, this project will create a publicly available 3D atlas of orofacial brainstem neurons, yielding lessons about the nature vital brain functions and of neuronal computation.

SABER: Scalable Analytics for Brain Exploration Research using X-Ray Microtomography and Electron Microscopy Gray Roncal, William R Johns Hopkins University 2017 Active
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Neuroimaging techniques are advancing at a rapid rate, resulting in high resolution images of brain tissue and large datasets that can be difficult to manage. William Gray Roncal’s team propose an integration framework called SABER: Scalable Analytics for Brain Exploration Research. With a focus on techniques (e.g., electron microscopy) that produce high resolution brain images, SABER will create a unified framework by which these data types are accessible to a broader audience, can be processed in a reproducible, portable way, and can be scaled from small data volumes to large datasets. SABER has the potential to enable discoveries from high-resolution imaging techniques, making the parsing of entire brains a new reality.

Sensorimotor processing, decision making, and internal states: towards a realistic multiscale circuit model of the larval zebrafish brain Engert, Florian (contact) Lichtman, Jeff W Sompolinsky, Haim Harvard University 2017 Active
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Understanding animal behavior requires a comprehensive look at the neural mechanisms that govern behaviors across spatial and temporal scales. Florian Engert and a team of experts are planning to generate a multi-level circuit model of the larval zebrafish brain by building on previous BRAIN work in which they integrated behavioral assays with whole-brain imaging and electron microscopy. Here, they plan to use these methods to understand additional relevant behaviors, including phototaxis, rheotaxis, escape, and hunting. Then, they will investigate how these behaviors interact in the presence of conflicting stimuli. Finally, they will study how internal states (e.g., hunger, stress or loneliness) can modulate each specific behavior, as well as their interaction. Together, this work will provide a thorough look at how complex behavior arises from the synapse to the whole brain level.
Sensory recruitment by working memory: neuronal basis and neural circuitry Noudoost, Behrad University Of Utah 2019 Active
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Maintaining working memory is crucial for performing everyday tasks, but we still do not understand the interactions between the prefrontal and visual cortices that are key for this process. Dr. Noudoost and colleagues will combine neurophysiological recordings, microstimulation and pharmacological manipulation, and computational modelling to study how the prefrontal cortex drives changes in the activity of visual areas during working memory tasks and how those changes affect behavior.

Single Neuron Analyzer for Multi-modal, Cross-dataset (Epi)genomic Cell Type Datasets Mukamel, Eran A University Of California, San Diego 2019 Active
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The characterization of single neurons is a major theme of research in the BRAIN Initiative Cell Census Network. Dr. Mukamel and team develop Single Neuron Analyzer (SNA), a cloud-based computer tool for interactive data exploration, analysis, and validation for single cell molecular data generated by the BRAIN Initiative. The software specifically implements machine learning and cross-validation techniques to improve the reproducibility of neuronal cell type identification.

Spatiotemporal Coding in the Pain Circuit Along the Spine-brain Continuum Borton, David Allenson Saab, Carl Y (contact) Rhode Island Hospital 2018 Active
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Neuropathic pain is a national health challenge for which there are limited effective therapeutics, and understanding the mechanisms of pain circuity is a critical step towards developing clinical interventions. Drs. Carl Saab and David Borton will develop electrophysiology and imaging tools that permit long-term investigation of spinal cord pain circuits in awake, behaving mice. In particular, these tools will pair real-time recording from inhibitory neurons in the spine-brain continuum with behavioral tasks to assess the link between sensory thalamocortical rhythms and pain stimuli. By identifying dynamic and functional connectivity in brain-spine neural circuits in the context of behavioral tasks, this work could enhance our understanding of how circuits create and contribute to pain perception and behavior, ultimately paving the way towards treatment.

Spatiotemporal control of dendritic inhibition by a family of diverse somatostatin-expressing interneurons Rudy, Bernardo NEW YORK UNIVERSITY SCHOOL OF MEDICINE 2018 Active
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Due to technical challenges, studying the circuits that mediate cortical computations has been restricted to the superficial layers of the cortex. Recently, Dr. Bernardo and team have utilized a novel method, known as channelrhodopsin-assisted patching or ChAP, that permits&nbsp;in vivo&nbsp;recording and labeling of genetically-tagged neurons throughout the brain, including entire cortical columns. The team will use ChAP recordings in awake head-restrained mice, as well as dynamic calcium imaging and electrophysiology, to study inhibitory neuronal circuits in layer 5 pyramidal cells in the somatosensory barrel cortex. The researchers will use paired recordings, optogenetic manipulations, and morphological analysis in acute slices to create circuit maps. Furthermore, they intend to utilize the experimental results to develop models of these cortical networks, which could be applied to understanding of other brain areas.

 

Spatiotemporal signatures of neural activity and neurophysiology in the BOLD signal Keilholz, Shella D Emory University 2016 Active
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Blood oxygenation level dependent (BOLD) MRI fluctuations used in mapping functional brain connectivity contain a wealth of information about neural activity. Most functional connectivity studies focus on detecting activity related to cognition and information processing, and view the presence of other contributors to the BOLD signal as a nuisance. However, evidence is growing that sources of “noise” in the BOLD signal contain clinically relevant information. Keilholz and her colleagues propose to combine a variety of imaging techniques in the rat brain in order to separate the usually discarded portions of BOLD fMRI fluctuations into four components with different spatial and temporal scales. The researchers hypothesize that each component may be affected in a different way by neurological and psychiatric disorders, so that the isolation of these components may improve the diagnosis and evaluation of brain dysfunction.
Spinal Circuits for the Control of Dextrous Movement Goulding, Martyn D Salk Institute For Biological Studies 2019 Active
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Motor circuits in the cervical spinal cord control many essential behaviors, such as skilled reaching and grasping. However, the cervical spinal cord remains an understudied region of the central nervous system. Dr. Goulding and team (the Spinal Cord Circuit Team, TeamSCC) will generate a novel atlas to study circuit dynamics and functional connectome of premotor and motor neurons of cervical spinal circuits controlling forelimb movements in rodents. This searchable, web-based portal will contain 3D visualization tools linked to molecular, electrophysiological, functional, and network model databases. These studies will inform ongoing research of motor control and brain function, leading to a better understanding of the motor system and how it is affected by neurological diseases and spinal injuries. 

Striatal Plasticity in Habit Formation as a Platform to Deconstruct Adaptive Learning CALAKOS, NICOLE DUKE UNIVERSITY 2018 Active
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The striatum receives direct input from many cortical and thalamic areas and is a major contributor to behaviors involving movement and learning. The striatum and its connections are implicated in diseases and disorders like Parkinson’s disease, Huntington’s disease, addiction, and compulsion. Whereas traditional forms of striatal plasticity involve the activity of direct and indirect medium spiny neurons, Dr. Calakos and team recently discovered that an increase in the excitability of local fast-spiking inhibitory interneurons plays an important role in habit learning – a paradigm that they have termed dviLP (direct vs indirect Latency Plasticity). Their novel tools – namely DISCO (Dual-pathway Imaging of Striatal Circuit Output) and DART (Drugs Acutely Restricted by Tethering) – should allow them to map, model, and manipulate striatal functional circuits during habit learning.

Structural and functional connectivity of the social decision-making network Smith, Adam Steven University Of Kansas Lawrence 2019 Active
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The formation of social relationships requires displays of commitment from social partners, yet we understand little of how neural networks function to regulate these context-appropriate social behaviors. Dr. Smith et al. aim to use the socially monogamous prairie vole as a model organism to study the neural mechanisms underlying social decision-making. The study will involve simultaneous fast measurement and manipulation of neural activity through real-time recordings and the alteration of neurochemical inputs within social decision-making networks. The work may help scientists better understand the brain circuitry that underlies social behavior.

Structural, single-cell transcriptomic, and functional 3-photon mapping of spinal pain circuits Kara, Prakash Kodandaramaiah, Suhasa B Vulchanova, Lyudmila H (contact) University Of Minnesota 2019 Active
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The Vulchanova, Kara, and Kodandaramaiah labs aim to study networks of neurons in the spinal cord that control transmission of pain signals to the brain. Their multi-disciplinary approach involves advanced genetic tracing techniques to map the cell’s wiring diagrams; calcium imaging to monitor circuit activity during pain; and single cell transcriptomics to analyze the gene activity of the cells in the circuits. Their results may help researchers understand how the nervous system process pain.

Studying perceptual decision-making across cortex by combining population imaging, connectomics, and computational modeling Harvey, Christopher D (contact) Lee, Wei-chung Allen Panzeri, Stefano Vt Harvard Medical School 2018 Active
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Perceptual decision-making involves groups of neurons working together in microcircuits to encode and transform sensory information into behavioral choices. However, the neural dynamics that allow for sensory-to-choice transformations remain poorly understood. Drs. Christopher Harvey, Wei-Chung Lee, Stefano Panzeri and team will perform two-photon calcium imaging of the mouse visual cortex (V1; sensory cortex) and posterior parietal cortex (PPC; association cortex) during a newly developed virtual- reality navigation task and build a computational network model to identify neurons that contribute to the sensory-to-choice transformations. Connectomics datasets comparing V1 and PPC, calcium imaging data from large populations during decisional tasks, and new computational frameworks of cortical microcircuits will allow for a better understanding of the neural mechanisms involved in perceptual decision-making.

Subcellular Mapping and Post-Synaptic Impacts of Striatal Dopamine Release During Behavior Vu, Mai-anh Boston University (charles River Campus) 2019 Active
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Dopamine (DA) inputs in the midbrain influence striatal activity in the basal ganglia, and dysfunction in this system is associated with many neurological and psychiatric illnesses. Dr. Vu aims to measure dopamine release onto the dendrites of single striatal neurons in real-time using 2-photon microscopy, and map functionally-relevant dopamine release onto striatal dendrites during different behaviors in mice. This work will inform our understanding of the spatial organization of dopamine inputs onto single neurons in the striatum, as well as how these inputs affect post-synaptic cell firing.

Subiculm circuits for cortical feedback regulation of spatial mapping and learning Nitz, Douglas Arthur Xu, Xiangmin (contact) University Of California-irvine 2018 Active
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Degeneration of the subiculum, a sub-region of the hippocampal formation, has been implicated in Alzheimer's disease progression. In freely-moving rodents, Xu’s team will study the unique subiculum circuits that mediate cortical regulation of hippocampus-associated spatial navigation and learning. Using advanced approaches for genetic targeting of specific cell populations (i.e., sub-types of subiculum neurons), and molecular and viral tracing techniques, the team will generate a detailed map of the synaptic circuit organization for the pathway from the retrosplenial cortex, to the subiculum, and to the hippocampal CA1 region. This research may help improve understanding of the neural circuit mechanisms underlying Alzheimer's disease.
Subthalamic and corticosubthalamic coding of speech production Richardson, Robert Mark University Of Pittsburgh At Pittsburgh 2016 Active
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Evidence points to an important role for the basal ganglia (BG) in speech. For instance, deep brain stimulation (DBS) of the subthalamic nucleus (STN) within the BG can improve motor symptoms for patients with Parkinson’s disease, but often does not improve speech impairments and in fact can disrupt language function. Richardson proposes to develop a model for how the BG helps drive speech production by recording activity of individual neurons within the STN along with STN and cortical local field potentials, in patients with Parkinson’s disease undergoing surgery to implant a DBS device. This work could lead to improved treatment for speech impairments in movement disorders, and reduced speech-related side effects of DBS therapy.
Taking DISCO Live: Dual pathway Imaging of Striatal Circuit Output in vivo Calakos, Nicole Duke University 2018 Active
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Physicians currently use therapies that satisfactorily target the basal ganglia to treat movement disorders, but more effective treatments elude clinical implementation due to major gaps in our understanding of functional principles for basal ganglia circuits. Calakos and colleagues will apply in vivo electrophysiological recording, optical activity imaging, and optogenetics to study plasticity of basal ganglia circuitry. The team will develop an approach to image striatal projection neuron activity in the basal ganglia in mice during the formation of a habitual behavior. They will then monitor and manipulate the relative timing-to-fire between two classes of striatal projection neurons and test the behavioral consequences. The knowledge and methodology gained from this project could help reveal new mechanisms for striatal plasticity, which may inform future therapeutic targets for movement and neuropsychiatric disorders.
Thalamocortical and corticocortical mechanisms for sleep-dependent visual learning Aton, Sara J University Of Michigan 2018 Active
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It remains unclear how sleep-associated changes in the activity of specific brain circuits contribute to consolidation of transient sensory experiences into long-lasting memories. Using freely-behaving mice, Aton’s team will test the necessity and sufficiency of sleep-associated thalamocortical activity patterns in consolidating a simple form of experience-dependent plasticity. With cutting-edge optogenetic strategies, in vivo electrophysiology, and novel computational tools, the researchers will characterize and selectively manipulate state-specific interactions between neurons, and evaluate how these interactions (and the network dynamics they regulate) drive sensory plasticity and learning. This work has the potential to lead to better understanding of psychiatric disorders where sleep and cognition are affected, including schizophrenia, depression, autism, and dementia.
Thalamocortical state control of tactile sensing: Mechanisms, Models, and Behavior Stanley, Garrett B. Georgia Institute Of Technology 2018 Active
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The complex circuit interconnecting the brain’s thalamus and cortex (etymology: connecting the inner chamber to the rind) is continuously controlled by inputs that fundamentally shape information processing necessary for perception and behavior. However, the precise link between thalamic state and the resulting sensory representations in the cortex remains an unanswered question in neuroscience. Using the vibrissa system (facial whiskers) in awake mice, Garrett Stanley and colleagues will optogenetically modulate thalamic activity and, using electrophysiological and optical measurements, explore the downstream impact on cortical representations and subsequent perception, as well as measure sensory behavioral tasks. This project’s success may help us understand nervous system disorders in which individuals exhibit loss of sensitivity and the ability to adapt to changes in the sensory environment.
The Application of Generalized Linear Models to Calcium Imaging Data for Optimal High-Dimensional Receptive Field Estimation and Identification of Latent Network Dynamics Keeley, Stephen L Princeton University 2017 Active
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Dr. Keeley plans to develop and make publically available an efficient and flexible statistical framework to guide analysis of calcium imaging data, extending researchers’ ability to track the activity of hundreds or thousands of neurons at various spatial scales.
The Brainstorm Project: A Collaborative Approach to Facilitating the Neuroethics of Bioengineered Brain Modeling Research Hyun, Insoo Case Western Reserve University 2018 Active
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Organoids, grown in laboratory settings to resemble parts of the developing human brain, hold great potential for shedding light on human brain function and disease. Researchers are working to achieve key bioengineering advancements, including successful vascularization of brain organoids, generating the full complement of cell types present in a human brain, and recording and modulating neural activity in organoids. These anticipated advances in bioengineered human brain modeling research may raise ethical questions about the moral status of large, complex human brain organoids and ethical boundaries on manipulating increasingly realistic engineered brain models. In this project, Dr. Hyun will lead proactive ethical discussions among ethicists and the neuroscientists conducting this cutting-edge work to develop greater awareness and understanding of these ethical implications and to inform future management of ethical issues that may be unique to this novel area of brain research.

The cerebro-cerebellar-basal-gangliar network for visuomotor learning Fusi, Stefano Goldberg, Michael E. (contact) Strick, Peter Columbia University Health Sciences 2019 Active
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Learning that a particular object cues a particular action, such as a red light cueing us to stop, is critical to our ability to function in the world. This project aims to use physiological, computational, and anatomical methods to investigate how brain regions (prefrontal cortex, basal ganglia, and cerebellum) work as a network to assign symbols to a particular movement or behavior. This will be done by mapping the various components of the network, perturbing individual nodes of the network to tease apart individual roles in the process, and developing f computational models to analyze the activity of all regions simultaneously. This work will advance our understanding of the circuit basis of visuomotor learning.

The diversity of dopamine neurons: from connectivity and activity to functions. Uchida, Naoshige HARVARD UNIVERSITY 2018 Active
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Dysfunction in the dopamine system is implicated in several neurological disorders, including addiction, depression, and schizophrenia. Dr. Uchida and team will investigate the diversity of dopamine neurons, examining their connectivity and activity patterns, along with their functions. The experiments will focus on dopamine neurons projecting to the posterior ‘tail’ of the striatum and those projecting to the ventral striatum during a variety of behavioral tasks in mice, including classical conditioning, nose-poke choice behavior based on outcomes, and novel object exploration. Their techniques, including optogenetics, fiber photometry, electrophysiology, and calcium imaging, may help build a computational and theoretical framework for understanding the scope of dopamine neuron function.

THE DYNAMICS OF LONG RANGE CORRELATIONS IN CORTEX: SINGLE UNITS AND OXYGEN Snyder, Lawrence H Washington University 2017 Active
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The brain is always active. Intrinsic, on-going correlated neural activity interacts with on-demand, task-specific processing, but it remains unclear how neuronal activity gives rise to resting state network dynamics. Lawrence Snyder and colleagues are utilizing miniaturized, high-channel-count carbon fiber arrays that are implanted in the awake monkey to simultaneously record oxygen level, spikes, and local field potentials. This novel methodological approach in hardware will permit the researchers to investigate which cells give rise to intrinsic activity, and how that activity differs when the animal is at rest or performing a task. By examining the cellular contributions to the brain in these states, this work has the potential to formulate a detailed characterization of the underlying dynamics of neural activity.
The Neural Mechanism of Interval Timing in Drosophila Smart, Ashley Danielle Stanford University 2019 Active
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Many organisms are capable of interval timing, as it is essential to many tasks important for survival. However, no research has determined a neural mechanism for this process.  Dr. Smart will study the neural mechanisms of interval timing in a coordinated network throughout the brain, and how these estimates of time affect behavior. The work will leverage behavioral assays, whole-brain neural activity imaging, and genetic techniques in the Drosophila brain. These findings will improve our understanding of how the brain keeps time.

The Neuroimaging Data Model: FAIR descriptors of Brain Initiative Imaging Experiments Keator, David Bryant University Of California-irvine 2019 Active
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Inconsistent terminologies of neuroimaging metadata prevent the precise description of the design and intent of an experiment, experimental subject characteristics, and the data acquired. Dr. Keator and colleagues aim to address this problem by developing human neuroimaging domain-specific controlled vocabularies. This will greatly improve our ability to search across datasets; to reuse, compare and integrate data across studies and sites; and to replicate neuroscience findings. They also aim to promote the adoption of the controlled vocabularies through community engagement.

The Neuronal Underpinnings of Non-invasive Laminar fMRI Yacoub, Essa University Of Minnesota 2018 Active
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Understanding the neural circuitry of the brain behind abilities such as perception, decision-making, and language requires high-resolution neuroimaging capabilities that have, thus far, been confined to animal models. This precedent makes it difficult to study uniquely human functions, such as language. Dr. Yacoub and a team of investigators will pair high-resolution functional magnetic resonance imaging (fMRI) with electrophysical recordings within the same participants, enabling the study of different cortical layers and their contributions to cognitive function. By using these cutting-edge techniques to build a reliable and generalizable model of layer-specific neural activity, the researchers will be able to better understand the mechanisms of layer-specific activation within and across brain regions.

The role of patterned activity in neuronal codes for behavior Maunsell, John Hr University Of Chicago 2014 Complete
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Dr. Maunsell's team will explore how large populations of neurons process visual information, using a newly developed light stimulation technique to induce brain cell activity in the visual cortex of mice.
the self-tuning brain: cellular and circuit mechanisms of behavioral resilience Fairhall, Adrienne L Gardner, Timothy James Lois, Carlos (contact) California Institute Of Technology 2017 Active
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In some instances, the brain can adapt to functional losses after neurological disease or injury, and recover normal behavior. Carlos Lois and colleagues will explore, in songbirds, the neuronal mechanisms by which the brain maintains stable behaviors after perturbation of function using gene delivery, optogenetics, in vivo functional imaging, electrophysiology, behavioral analysis, and computational modelling. They will introduce a variety of perturbations (including real-time optogenetic perturbations as well as permanent genetic perturbations) to high vocal center neurons, and study behavioral and circuit responses, as well as cellular and circuit properties of song restoration. They will then generate quantitative theoretical models to account for the behavioral resilience. This research is relevant to the pursuit of new avenues for treating neurological diseases.
Time-Gated Diffuse Correlation Spectroscopy for functional imaging of the human brain Franceschini, Maria Angela Massachusetts General Hospital 2019 Active
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Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method that allows scientists to study brain activity through hemodynamic changes but encounters technological limitations. To improve upon the capabilities of fNIRS, Dr. Franceschini and a team of investigators will develop functional diffuse correlation spectroscopy, which measures the fluctuations in light scattering that occur as red blood cells move. The team aims to first characterize this technology in mock tissue, before validating it in healthy volunteers against other non-invasive imaging methods. Successful of this technological approach will enable cerebral blood flow measurements that can occur with greater sensitivity, better spatial resolution, deep inside the brain - allowing for an unprecedented tool to characterize human brain function.

Tools for modeling state-dependent sensory encoding by neural populations across spatial and temporal scales David, Stephen V (contact) Mesgarani, Nima Oregon Health & Science University 2019 Active
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Humans and other animals adapt their hearing in noisy environments, but the mechanisms underlying this central auditory process are not well understood. Here, Dr. Stephen David and his team will develop computational tools to understand how the neural populations in the healthy brain represent complex natural sounds. The group will build a software library that can model the functional relationship between auditory stimuli and corresponding neural responses, for which there are few existing models that effectively measure comparisons between the two. The system will also support machine learning methods that will be valuable for large-scale signal processing problems. These experiments will provide novel insight into how the brain solves problems that will allow engineering of new devices and treatments for conditions involving auditory dysfunction.

Toward a Theory for Macroscopic Neural Computation Based on Laplace Transform Howard, Marc W Boston University (charles River Campus) 2016 Active
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Behavioral and cognitive experiments suggest that a number of sensory processes follow Weber-Fechner scaling, which states that as the intensity of an actual stimulus increases linearly, the intensity of our perception increases only logarithmically. Yet, how the brain transforms linear changes in stimuli intensity to logarithmic changes in perception is not entirely understood. Nor is it known whether other cognitive processes like memory also follow some form of Weber-Fechner scaling. Howard and his colleagues plan to develop a theoretical means for understanding logarithmic sampling by sensory systems in the interpretation of neural data. The hope is that this understanding will provide insight into basic neurophysiological processes and how the brain both represents the past and predicts the future, which can be relevant to diseases involving memory loss and disturbances in health-related decision making.
Towards a Complete Description of the Circuitry Underlying Memory replay. Soltesz, Ivan University Of California-irvine 2014 Complete
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Dr. Soltesz's team will combine computer brain modeling and large-scale recordings of hundreds of neurons to understand how the brain generates sharp-wave-ripples, a neuronal activity pattern essential for learning and memory.
Towards a Complete Description of the Circuitry Underlying Sharp Wave-Mediated Memory Replay Buzsaki, Gyorgy Lisman, John E Losonczy, Attila Schnitzer, Mark J Soltesz, Ivan (contact) Stanford University 2017 Active
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In mammals, it has been difficult to address how neurons function as a network to produce cognition, and there are no circuit mechanisms of mammalian brain signals that are understood to the same degree as in simple systems such as invertebrates. Ivan Soltesz and a team of experts are using large-scale recordings and optical monitoring to elucidate subcellular events and probe the sharp-wave ripple (a hippocampal signal associated with memory consolidation) in awake, behaving animals. As part of this project, the team will use supercomputers to generate a full-scale computational model that links sharp-wave ripples to memory replay. This project has the potential to provide a detailed look at the principles by which neurons coordinate signals to produce cognitive function.
Towards a unified framework for dopamine signaling in the striatum Sabatini, Bernardo L (contact); Assad, John ; Datta, Sandeep R; Gershman, Samuel J; Linderman, Scott Warren; Uchida, Naoshige ; Wilbrecht, Linda E Harvard Medical School 2019 Active
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Dopamine has many important functions in the brain, particularly those involving movement and reward. Dopaminergic neurons and the activity of dopamine have been proposed to reinforce the actions and sensory context associated with reward, trigger the execution of motor actions, and control the vigor, strength, and timing of motor actions. Dr. Sabatini will lead an exceptional team of investigators to develop a quantitative model of dopaminergic circuits and dopamine function. They aim to determine what features of the environment, reward history, reward expectation, and motor action are encoded in the activity of ventral tegmental area (VTA) and substantia nigra pars compacta (SNpc) dopaminergic neurons – as well as the effects on downstream targets in the striatum – in mice. The project will develop an efficient and comprehensive framework to readily share data, protocols, instrumentation designs, code, and biological resources with the neuroscience community.  

Ultra High Resolution Brain PET Scanner for in-vivo Autoradiography Imaging El Fakhri, Georges MASSACHUSETTS GENERAL HOSPITAL 2018 Active
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Current research and clinical positron emission tomography (PET) neuroimaging relies on whole-body scanners, with image resolution that is sub-optimal for a comprehensive, detailed look at the human brain. Drs. Georges El Fakhri, Roger Lecomte, and a team of investigators propose the development of a dedicated brain PET scanner with ultra-high resolution, to be unmatched by existing PET scanners and improving resolution and sensitivity by an order of magnitude. The group will design, build, and benchmark this next-generation PET scanner based on hardware advances by members of their collaborative team, before piloting the system in human subjects. The new system has the potential to elucidate key structures in neurotransmitter systems that currently cannot be imaged accurately with PET.

Uncovering Population-Level Cellular Relationships to Behavior via Mesoscale Networks Carlson, David E Duke University 2019 Active
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In complex neural circuitry, it is not clearly understood how the activity of individual neurons coordinate with larger networks to ultimately give rise to behavior. Here, Dr. David Carlson and his team will study how neurons’ action potentials, long considered to be a fundamental unit of information, relate to whole-brain spatiotemporal voltage patterns and behavior. To uncover this relationship, they will develop novel computational methods capable of creating generalizable maps that relate voltage signals from multiple brain regions based upon machine learning approaches. These network maps then will be used to classify neurons and employ statistical approaches to uncover meaningful relationships across scales of neural activity and behavior with relevance to health and disease.

Understanding Brain Development Through the Lens of Metabolism Bhaduri, Aparna University Of California, San Francisco 2019 Active
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Recent advances in sequencing technology are revealing diverse cell types across the human and mouse brains, with some transient progenitor cell types found to exist only during development. In addition to this diversity of cell types, early evidence points to diversity in lipid expression and function throughout the brain. Dr. Bhaduri aims to characterize the developing human cortex across multiple regions, linking differences in transcriptomic and lipidomic data in order to understand how metabolism and transcriptional regulation interact to determine cell fate decisions in cortical progenitors. The work will offer insight into how the human brain develops.

Understanding evoked and resting-state fMRI through multi scale imaging Constable, R. Todd (contact) Crair, Michael Hyder, Dewan Syed Fahmeed Yale University 2016 Active
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For decades, functional MRI (fMRI) has been the most powerful and ubiquitous technique for measuring whole brain activity. However, the biological activity underlying the fMRI signal is unclear. Constable and his team will probe the brain with a novel device that combines high-resolution calcium imaging—a technique that measures a proxy of electrical activity in neurons—across the entire cortex along with fMRI in mice. These measurements will identify the contributions of different cell populations (excitatory, inhibitory, and glial cells) to the fMRI signal. In addition, the team will use cutting-edge tools to knock out specific neural nodes to test the validity of fMRI-generated maps of connectivity between brain regions. This work will provide new insights into the biological basis of fMRI and improve our understanding of the functional organization of the healthy human brain.
Understanding how post-translational palmitoylation influences in vivo molecular and circuit dynamics during learning Nelson, Jessica C University Of Pennsylvania 2019 Active
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Habituation is a form of learning by which organisms become less responsive to repetitive stimuli. While often impaired in disorders with complex cognitive symptoms, and thus has relevance to human disease, there are significant gaps in the understanding of habituation learning. To address this challenge, Dr. Nelson will study the critical role of protein modifications in habituation learning, using larval zebrafish as a model system. The project will involve training in protein modification and in vivo electrophysiology, integrating these approaches into a well-rounded system to examine learning across genes, circuits, and behavior. Success of the project may reveal how post-translational protein modifications influence synaptic plasticity within defined neural circuits as we learn.

Understanding the logic of the brain-wide olfactory bulb projectome Albeanu, Dinu Florentin (contact) Koulakov, Alexei Cold Spring Harbor Laboratory 2019 Active
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It remains unclear how information from odors are processed by the brain regions that make up our olfactory system. Using high-throughput sequencing methods, in vivo functional imaging, and anatomical and computational tools, this project aims to study how cells in the olfactory bulb extract information from odors and then send this information to other parts of the brain for processing.

Understanding the Neural Basis of Volitional State through Continuous Recordings in Humans Cash, Sydney S Massachusetts General Hospital 2016 Active
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  • Monitor Neural Activity
Every day, humans make many cognitive shifts of their own volition. Examples are as diverse as changes in wakefulness to planning complex movements. Current research often explores only neural activity that is associated with behavior using fixed, externally-driven models. Dr. Sydney Cash’s team will capitalize on data from patients who already have implanted electrodes to investigate the neural basis for voluntary cognitive shifts by first examining activity during directed versus spontaneous motor acts, and then moving into language processing. The group plans to simultaneously improve and expand upon human neuronal recording technologies to enable more continuous, real-time studies, which has implications for our understanding of fundamental mechanisms underlying cognitive neuroscience, as well as various neuropsychiatric disorders and brain-machine interfaces.
Understanding the synaptic, cellular and circuit events of MEG & EEG using a vertically translational cross-species approach Doiron, Brent D. Salisbury, Dean F Teichert, Tobias (contact) University Of Pittsburgh At Pittsburgh 2017 Active
  • Monitor Neural Activity
  • Integrated Approaches
  • Human Neuroscience
In healthy humans, if an identical auditory stimulus is repeated within 8-12 seconds, electroencephalography/magnetoencephalography (EEG/MEG) measured response to the second occurrence is attenuated. It is unclear how this attenuation is represented at synaptic, single-cell, and circuit levels, or what it reveals about local circuit and network wiring principles. Tobias Teichert’s team will study auditory-evoked response modulation in human, rhesus monkey, and large-scale neural models, testing whether repeated-stimuli response attenuation is caused by synaptic depression at cortical synapses, and whether synaptic depression depends on circuit and network architecture. They will analyze system-level and brain-region-level EEG/MEG, circuit-level local field potentials, single-neuron firing rates, and synaptic function. Because reduced modulation of EEG/MEG amplitude by past stimuli is associated with schizophrenia, understanding the relationship between EEG/MEG and neuronal events could benefit neurological/psychiatric disease research.
Understanding V1 circuit dynamics and computations Miller, Kenneth D (contact) Scanziani, Massimo Columbia University Health Sciences 2018 Active
  • Integrated Approaches
The primary visual cortex (V1) is an extensively studied cortical area, yet current models poorly capture how V1 neurons respond to complex stimuli, such as natural scenes. Miller, Scanziani, and colleagues will combine new technologies for genetically identifying cell types in mouse V1, as well as monitoring and manipulating V1 neural circuits using tools like multi-photon holographic optogenetics. The team will pursue the necessary experimental data (i.e., synaptic connectivity and physiological responses of all V1 cell types) to build predictive models of how V1 dynamics form the basis of vision. Moreover, they aim to establish a generalizable paradigm for understanding any cortical area. If successful, this collaborative effort of experimentalists and theorists will achieve new insights into visual cortical function and dynamics that could help in understanding the origins of various neurological disorders.
Using Direct Brain Stimulation to Study Cognitive Electrophysiology Kahana, Michael Jacob University Of Pennsylvania 2019 Active
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity

Diseases of memory and cognition are among the most devastating for patients and families, but the complexity of dynamic neural circuits that give rise to cognition creates challenges for effective therapeutic and clinical interventions. Dr. Michael Kahana and his team propose a multi-site, collaborative effort to uncover the neural processes underlying different forms of memory. They aim to use both direct intracranial stimulation and dynamical modeling to definitively identify brain activity that is causally linked to cognition. In a safe and ethically sound recruitment of patients undergoing otherwise therapeutic surgery, the success of this project will inform a theoretical framework for simulating the interaction between direct electrical stimulation and human neurophysiology, as well as insights and specific targets for future cognitive therapies.

Using fMRI to Measure the Neural-level Signals Underlying Population-level Responses Cowell, Rosemary Alice (contact) Huber, David Ernest University Of Massachusetts Amherst 2017 Active
  • Monitor Neural Activity
  • Integrated Approaches
  • Human Neuroscience
In spite of the ability of functional magnetic resonance imaging (fMRI) to relate neural systems to human behaviors, this relationship is indirect because it follows the neurovascular response rather than directly recording the activity of neurons. Rosemary Cowell’s team will develop and validate a technique for using fMRI in humans to determine how neural-level responses modulate with behavior. The group will model how changes in the voxel-level blood oxygenation-level dependent (BOLD) signal reflect changes in neural-level tuning functions. This research will advance the ability to accurately and precisely infer the properties of neuronal signals—associated with changes in perception, attention and cognition—underlying population-level fMRI data.
Using functionally-defined glomeruli to probe circuit function in the mammalian olfactory bulb WACHOWIAK, DALE UNIVERSITY OF UTAH 2018 Active
  • Integrated Approaches

Olfactory information is first processed in the olfactory bulb (OB), where the primary olfactory sensory neurons project. Using transgenic mice, improved calcium imaging techniques, and a novel method for rapidly and flexibly presenting large numbers of odorants, Dr. Wachowiak and team will define functional maps of sensory neuron inputs to OB glomeruli to understand how OB circuits shape glomeruli output, as well as how odor experiences shape the glomeruli circuits. Furthermore, results from these experiments will lead the team to develop modeling frameworks to understand the organization and behavior of olfactory circuits.

Ventromedial prefrontal cortex regulation of fear memory expression Cummings, Kirstie Alyssa Icahn School Of Medicine At Mount Sinai 2019 Active
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools

Traumatic events can result in anxiety disorders, including post-traumatic stress disorder (PTSD), a hallmark of which is amplified expression of fear and resistance to behavioral therapies. While the ventromedial prefrontal cortex (vmPFC) is thought to have a fear-inhibiting role, activity in its subregions is also elevated in many PTSD patients. To understand this functional dichotomy, Dr. Cummings will investigate the mechanisms by which vmPFC subregions encode learned fear by using a range of approaches, including calcium imaging, circuit tracing, in vivo optogenetic manipulation, and ex vivo electrophysiology in mice. Success of the project should result in characterization of the role of vmPFC in the regulation of fear memory, which may inform existing models of fear circuitry and help elucidate the mechanisms that are recruited in fear learning.

Vertically integrated approach to visual neuroscience: microcircuits to behavior Euler, Thomas Huberman, Andrew D Meister, Markus Seung, Hyunjune Sebastian (contact) Wong, Rachel O Princeton University 2014 Complete
  • Cell Type
  • Circuit Diagrams
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools
Dr. Seung and colleagues Thomas Euler (U Tübingen), Andrew Huberman (UC San Diego), Markus Meister (Caltech), and Rachel Wong (UW Seattle) will use state-of-the-art genetic, electrophysiological, and imaging tools to map the connectivity of the retina, the light-sensing tissue in the eye. The goal is to delineate all the retina's neural circuits and define their specific roles in visual perception and behavior.
Viral Strategies for Functional Connectomics in the Visual System Reid, R Clay Allen Institute 2017 Active
  • Integrated Approaches
A fundamental unanswered question in neuroscience is how specific connections between neurons underlie information processing. Clay Reid and colleagues will study the functional logic of wiring within three cortical areas: the primary visual cortex, and the anterolateral and posteromedial visual areas, before examining the functional logic of connections between these areas. Inter-neuron connections will be determined by using a modified virus that specifically labels ensembles of neurons, all of which connect with a single pre-designated target neuron. The team will then use two-photon calcium imaging to make movies of each neuron's activity in response to carefully-chosen visual stimuli. The approaches developed here may improve researchers’ ability to study the relationship between altered inter-neuron connections and neurological and psychiatric functional deficits.
Visual coding in freely moving behavior Niell, Cristopher M University Of Oregon 2019 Active
  • Integrated Approaches

Studying how the brain processes visual information in a natural environment can be tricky because researchers cannot exactly see what a freely moving subject is seeing. The Niell group aims to address this problem by developing a head-mounted, dual miniature camera system that aims to simultaneously capture an animal subject’s visual scenery while also recording the subject’s corresponding eye positions.. Combining this data may help the researchers approximate what an animal saw so that they can compare the scenery to corresponding neural activity in the brain. The Niell group plans to test this system on freely moving and head fixed animals. The results may help researchers understand how a brain encodes visual information under more natural conditions.

Wireless High-Density Diffuse Optical Tomography for Decoding Brain Activity Culver, Joseph P Washington University 2018 Active
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
Functional neuroimaging is increasingly used as a diagnostic and prognostic tool in clinical populations, but traditional brain scanners (e.g., fMRI) require patients to remain motionless as images are acquired. Dr. Joseph Culver and colleagues propose the development of a wireless and wearable high-density diffuse optical tomography (HD-DOT) system for mapping brain functions in naturalistic settings. The group will address the technical challenges of developing a lightweight, wireless system, as well as validate paradigms needed to map and decode brain function within the system, before piloting the system in patients with cerebral palsy. By creating a portable system, this work has the potential to dramatically advance optical imaging and its role in understanding brain function – particularly in situations where it is difficult for patients to remain motionless.