Funded Awards

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Investigator
Ecker, Joseph R
Institute
Salk Institute For Biological Studies
Year Funded
2017
FOA Number
Status
Active
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
Summary

Dr. Ecker's group will use signatures of epigenetics, the switching on-and-off of genes in response to experience, in mouse frontal cortex to help identify different classes of cells and understand their function.

Investigator
Nasiriavanaki, Mohammadreza
Institute
Wayne State University
Year Funded
2019
FOA Number
Status
Active
Project Number
Priority Area
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
Summary

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.

Investigator
Kodandaramaiah, Suhasa B (contact) Mcalpine, Michael
Institute
Applied Universal Dynamics Corporation
Year Funded
2019
FOA Number
Status
Active
Project Number
Priority Area
  • Circuit Diagrams
  • Interventional Tools
  • Monitor Neural Activity
Summary

A mechanistic understanding of the neuronal underpinnings of sensory perception, action, emotion, and cognition requires measuring activities of these neuronal circuits at single cell resolution across several millimeters, and at multiple temporal scales. However, methods providing high spatial resolution often lack concurrent high temporal resolution and vice versa, creating technical challenges. Working with Applied Universal Dynamics Corporation, Dr.

Investigator
Gibson, Emily Welle, Cristin G (contact)
Institute
University Of Colorado Denver
Year Funded
2018
FOA Number
Status
Active
Project Number
Priority Area
  • Interventional Tools
  • Monitor Neural Activity
Summary

To further our understanding of how neural circuits function, we need tools that can collect simultaneous measurements from large populations of neurons involved in a common neural computation and provide precise functional modulation. Current optical imaging in awake animals expressing calcium indicators provides spatial and temporal precision, but limitations include small fields-of-view (encompassing single brain regions) and head-fixation requirements that prevents naturalistic behavior.

Investigator
Witte, Russell S (contact)
Institute
University Of Arizona
Year Funded
2019
FOA Number
Status
Active
Project Number
Priority Area
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
Summary

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.

Investigator
Blaauw, David
Institute
University Of Michigan At Ann Arbor
Year Funded
2018
FOA Number
Status
Active
Project Number
Priority Area
  • Interventional Tools
  • Monitor Neural Activity
Summary

Wireless, small, injectable neural recording modules have been a long-standing goal in neuroscience. Blaauw’s team presents a new approach for recording and transmitting neural signals at the single- neuron level, using fully-wireless, 100x100μm-sized micro-probe implants (mProbes). mProbes can be injected into the brain at nearly unlimited locations in the sub-arachnoid space.

Investigator
KATZ, PAUL
Institute
UNIVERSITY OF MASSACHUSETTS AMHERST
Year Funded
2018
FOA Number
Status
Active
Project Number
Priority Area
  • Integrated Approaches
Summary

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.

Investigator
BONINGER, MICHAEL
Institute
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
Year Funded
2018
FOA Number
Status
Active
Project Number
Priority Area
  • Human Neuroscience
  • Interventional Tools
  • Monitor Neural Activity
Summary

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.

Investigator
Clandinin, Thomas Robert Dickinson, Michael H (contact) Druckmann, Shaul Mann, Richard S Murray, Richard M Tuthill, John Comber Wilson, Rachel
Institute
California Institute Of Technology
Year Funded
2017
FOA Number
Status
Active
Project Number
Priority Area
  • Integrated Approaches
Summary
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.
Investigator
White, Owen R
Institute
University Of Maryland Baltimore
Year Funded
2017
FOA Number
Status
Active
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools
Summary

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.

Investigator
Huang, Eric J Kriegstein, Arnold (contact)
Institute
University Of California, San Francisco
Year Funded
2017
FOA Number
Status
Active
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
Summary
Scientists have yet to achieve high-resolution classification of the billions of neurons and non-neuronal cells in the human brain. To attempt this feat, Arnold Kriegstein and Eric Huang will perform high-throughput, droplet-based single-cell RNA and transposase-accessible chromatin sequencing techniques to collect genetic and epigenetic information from individual cells, which will be sampled from multiple regions of post-mortem human brains that are developmentally between early gestation and adolescence.
Investigator
Gee, James C Hawrylycz, Michael (contact) Martone, Maryann E Ng, Lydia Lup-ming Philippakis, Anthony
Institute
Allen Institute
Year Funded
2017
FOA Number
Status
Active
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
  • Theory & Data Analysis Tools
Summary
One major technical challenge for the BRAIN Initiative is the storage and dissemination of large amounts of data collected by different project teams. Hawrylycz and colleagues will support the cell census efforts of the BRAIN Initiative by hosting the BRAIN Cell Data Center (BCDC). Through the BCDC, they will store single-cell data on genetics, histology, electrophysiology, morphology, anatomical location, and synaptic connections from multiple species in a standardized manner. They will also develop and provide training for web-based tools to ease data visualization and analysis efforts.
Investigator
Gibson, Emily Kilborn, Karl (contact)
Institute
3 I
Year Funded
2019
FOA Number
Status
Active
Project Number
Priority Area
  • Circuit Diagrams
  • Interventional Tools
  • Monitor Neural Activity
Summary

Studies with freely-moving animals often encounter technical impediments that prevent the recording and perturbation of neural activity at cellular resolution. Working with Intelligent Imaging Innovations Inc (3I), Dr. Karl Kilborn and team will evaluate the feasibility of constructing a compact, stand-alone system that uses a laser source to perform fast, volumetric interrogation of cortical circuits in awake, behaving animals.

Investigator
Huang, Z Josh
Institute
Cold Spring Harbor Laboratory
Year Funded
2017
FOA Number
Status
Complete
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
Summary

Identifying individual cell types in the brain is a monumental task that is complicated by the limitations of current molecular technologies. To measure genetic diversity in the whole mouse brain, Huang and Arlotta will lead a team using next-generation droplet-based single-cell transcriptome sequencing along with other highly sensitive single-cell techniques that allow for high-throughput data collection. They plan to map these data onto the spatial locations of forebrain neurons with the help of high-resolution microscopy and genetically driven cell markers.

Investigator
Zeng, Hongkui
Institute
Allen Institute
Year Funded
2017
FOA Number
Status
Complete
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
Summary

The large number of cells in the brain and the complexity of their molecular and functional characteristics make it difficult to define individual cell types. Zeng and colleagues plan to complement high throughput droplet-based transcriptome survey with deep sequencing technique and multiplexed error-robust fluorescence in situ hybridization (MERFISH) to comprehensively characterize gene expression information from anatomically mapped cells across the entire mouse brain.

Investigator
Boas, David A Davison, Ian Gordon Tian, Lei (contact)
Institute
Boston University (charles River Campus)
Year Funded
2019
FOA Number
Status
Active
Project Number
Priority Area
  • Interventional Tools
  • Monitor Neural Activity
Summary

Watching the brain in action can help advance our knowledge of how neuronal activity produces behaviors but currently, long-term brain monitoring systems have a limited field of view. Here, the multidisciplinary collaborative group will create a novel head-mounted miniscope that will image large areas of the cortex in freely moving mice.

Investigator
Bruchez, Marcel P Ropelewski, Alexander J (contact) Watkins, Simon C
Institute
Carnegie-mellon University
Year Funded
2017
FOA Number
Status
Active
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools
Summary

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.

Investigator
Rokem, Ariel Shalom
Institute
University Of Washington
Year Funded
2019
FOA Number
Status
Active
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools
Summary

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.

Investigator
Lichtman, Jeff
Institute
HARVARD UNIVERSITY
Year Funded
2018
FOA Number
Status
Active
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools
Summary

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.

Investigator
Kimmel, Bruce
Institute
VIDRIO TECHNOLOGIES, LLC
Year Funded
2018
FOA Number
Status
Active
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
  • Human Neuroscience
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools
Summary

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.