Funded Awards

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Investigator
Sayler, Gary S
Institute
490 Biotech, Inc.
Year Funded
2018
FOA Number
Status
Active
Project Number
Priority Area
  • Circuit Diagrams
  • Interventional Tools
  • Monitor Neural Activity
Summary

To understand brain function, we need to be able to able to monitor cellular activity in the brain noninvasively over time.  To overcome these limitations Dr. Sayler's group will develop a set of self-exciting, continuously bioluminescent, optical imaging reporters that, unlike existing systems, are pre-engineered to support genetically encoded, autonomous, metabolically-neutral, neuron- or astrocyte-specific fluorescence that can be monitored with common laboratory equipment.

Investigator
Reid, R Clay
Institute
Allen Institute
Year Funded
2019
FOA Number
Status
Active
Project Number
Priority Area
  • Cell Type
Summary

Macroscale connectomics lacks cellular resolution, while microscale connectomics often lacks information about the source of inputs entering, or the targets of axons exiting the studied brain volume. Dr. Reid’s lab aims to tackle this problem through the development of a high-resolution 3D imaging technique to map antibody-stained axons over long distances. Using Dual Inverted Selective Plane Illumination Microscopy (diSPIM), the researchers propose to image and analyze visual cortical areas in macaque brain to create a dense axonal connectomics data set. The approach may allow whole-brain analysis of axonal projections with microscale connectomics, advancing our knowledge of how individual neurons communicate over long distances.

Investigator
Ringach, Dario L
Institute
University Of California Los Angeles
Year Funded
2016
FOA Number
Status
Active
Project Number
Priority Area
  • Integrated Approaches
  • Theory & Data Analysis Tools
Summary
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.
Investigator
Brunner, Peter Schalk, Gerwin (contact)
Institute
Wadsworth Center
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

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.

Investigator
Rinberg, Dmitry (contact) Shoham, Shy
Institute
New York University School Of Medicine
Year Funded
2014
FOA Number
Status
Complete
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
  • Integrated Approaches
  • Interventional Tools
  • Monitor Neural Activity
  • Theory & Data Analysis Tools
Summary
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.
Investigator
Heiney, Shane A
Institute
Baylor College Of Medicine
Year Funded
2017
FOA Number
Status
Active
Project Number
Priority Area
  • Integrated Approaches
Summary
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.
Investigator
Sommer, Friedrich T
Institute
University Of California Berkeley
Year Funded
2015
FOA Number
Status
Complete
Project Number
Priority Area
  • Theory & Data Analysis Tools
Summary
In their quest to understand the brain, neuroscientists continue to improve techniques for recording simultaneously from increasingly large numbers of neurons. This generates enormously large data sets. Analysis of these data sets will require new algorithms to understand how coordinated neural activity correlates to cognitive function. The goal of the course proposed by Sommer and colleagues is to identify, teach, and disseminate the best available methods for the analysis of large-scale neuroscience data sets. Their course will build on an existing course, "Mining and modeling of neuroscience data," and addresses a critical need by bringing individuals with quantitative backgrounds into the field of neuroscience.
Investigator
Fletcher, Preston Thomas
Institute
University Of Utah
Year Funded
2016
FOA Number
Status
Active
Project Number
Priority Area
  • Integrated Approaches
  • Theory & Data Analysis Tools
Summary
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.
Investigator
Kiani, Mehdi
Institute
PENNSYLVANIA STATE UNIVERSITY-UNIV PARK
Year Funded
2018
FOA Number
Status
Active
Project Number
Priority Area
  • Interventional Tools
  • Monitor Neural Activity
Summary

Large-scale monitoring and modulation of brain activity using non- or minimally invasive tools with high spatiotemporal resolution remains a challenge for neuroscientists. Dr. Mehdi Kiani and colleagues will develop a new bidirectional, neural-interface platform for electrophysiological recordings and stimulation of neural activities over the entire brain. This wireless, minimally invasive technology measures micro-electrocorticography signals from 100 sites, drives ultrasonic transducers to guide a focused ultrasonic beam to stimulate a targeted brain region, and simultaneously images the neural tissue – all at 500 mm resolution. The platform functions with an external unit in a closed-loop fashion to deliver the stimulation pattern, recover the electrophysiological and imaging data, and create the neural tissue images.

Investigator
SHOHAM, SHY et al.
Institute
NEW YORK UNIVERSITY SCHOOL OF MEDICINE
Year Funded
2018
FOA Number
Status
Active
Project Number
Priority Area
  • Interventional Tools
Summary

Large-scale neural recording and perturbation technologies can help us understand brain function. At present these technologies are limited to either single-cell or whole-brain level investigations. Shoham, Razansky, and Rinberg will leverage the deep tissue penetrability of ultrasound waves to develop an integrated system combining optoacoustic imaging and ultrasound neuromodulation. With the proposed device placed on the brain surface, researchers will collect optoacoustic tomographic data and perform holographic ultrasonic neural stimulation. This system will permit access to distributed neural activity deep within the rodent brain, including during an olfactory decision-making task. Direct and/or indirect access to neural activity over large volumes at extremely high imaging rates could be achieved, enabling new deep brain experiments that currently are not possible.

 

Investigator
Poldrack, Russell A
Institute
Stanford 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

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.

Investigator
Bronte-stewart, Helen
Institute
Stanford University
Year Funded
2019
FOA Number
Status
Active
Project Number
Priority Area
  • Human Neuroscience
  • Interventional Tools
  • Monitor Neural Activity
Summary

Gait impairment and freezing of gait (FOG) lead to falls, loss of independent living, and injury (even death) in patients with Parkinson’s disease (PD). These symptoms have limited treatment options that are not well addressed by current deep brain stimulation (DBS) methods. Dr. Bronte-Stewart and colleagues will test the feasibility of subthalamic nucleus (STN) neural and kinematic adaptive DBS (NaDBS and KaDBS, respectively) in PD patients, as well as the safety and tolerability of the use of dopaminergic medication in coordination with adaptive stimulation. This innovative approach using neuro-biomechanical features may enable the first clinical studies of bilateral STN aDBS for FOG, laying the groundwork for improved gait therapy in PD and other neurological disorders.

Investigator
Cullen, Daniel Kacy
Institute
University Of Pennsylvania
Year Funded
2015
FOA Number
Status
Complete
Project Number
Priority Area
  • Monitor Neural Activity
  • Interventional Tools
Summary
Traditional non-organic micro-electrodes can record and stimulate from many brain areas, but they produce inflammation, exhibit signal degradation, and lack specificity in neuronal cell type targeting. Cullen's project will develop "living electrodes" composed of neurons transfected with optogenetic reagents that can record and stimulate neural circuits. The neurons will be grown in tiny glass tubes and inserted into rodent cortex. If they make connections to cortical neurons, they could be used for selective recording and modulation of the native cortical circuits, which would enable targeting of specific host neuronal subtypes using custom tissue engineering to increase specificity to target neuronal populations.
Investigator
Hochgeschwender, Ute H (contact) Moore, Christopher I Shaner, Nathan Christopher
Institute
Central Michigan University
Year Funded
2016
FOA Number
Status
Active
Project Number
Priority Area
  • Monitor Neural Activity
  • Interventional Tools
Summary
Optogenetics and chemigenetics are powerful tools for precise control over neural activity in specific circuits. Hochgeschwender and her colleagues will develop and optimize a new class of hybrid opto-/chemi- genetic probes. Their strategy entails tethering a bioluminescent enzyme from fireflies (luciferase) to channel opsins that respond to light. Administration of a chemical substrate (luciferin) induces the opsins to either enhance or inhibit neuronal action potential firing, depending on the type of opsin to be used. With the continued development of new opsin and luciferase variants, this approach promises more flexibility and precision in experimental systems for testing circuit contributions to behavioral function and dysfunction in a variety of brain and psychiatric disorders.
Investigator
Chow, Brian Y Discher, Bohdana (contact)
Institute
University Of Pennsylvania
Year Funded
2016
FOA Number
Status
Complete
Project Number
Priority Area
  • Monitor Neural Activity
  • Interventional Tools
Summary
A key goal for the BRAIN Initiative is to be able to image neural activity from identified cell types in the brain. Discher and her colleagues propose a new strategy for genetically coded voltage sensors that exploits electron transport across protein domains rather than conformational shifts in protein structure. If this strategy is successful, the new indicators will report voltage changes on the order of microseconds, potentially matching the time-scale of fast action potentials in neurons. Once developed, these sensors will greatly advance optical imaging of neural activity, thereby accelerating progress toward understanding how brain activity governs human behavior, cognition, and brain disorders.
Investigator
Wester, Brock A.
Institute
Johns Hopkins 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

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.

Investigator
Cetin, Ali Haydar
Institute
Allen Institute
Year Funded
2017
FOA Number
Status
Active
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
  • Monitor Neural Activity
  • Interventional Tools
Summary
Studying vast numbers of functioning neurons in the brain requires precise spatio-temporal tools. Toward this end, researchers are interested in genetically modifying specifically selected cells in vivo, for neuronal subtype-specific, single-cell-level analysis. Cetin and colleagues will modify current genomic manipulation enzymes, making them light inducible, to achieve high-throughput single-cell genomic modification in response to brief pulses of light in the brain. They will generate transgenic mouse lines with these recombinases, use light to trigger site-specific DNA modification, and study the connections, morphology, function, and genetic identity of individual neurons within the brain. This approach may break technical barriers and has a range of potential applications, enabling enhanced precision in analyzing mammalian brain circuitry.
Investigator
Delorme, Arnaud Majumdar, Amitava Makeig, Scott (contact) Poldrack, Russell A
Institute
University Of California, San Diego
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

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.

Investigator
Chung, Moo K
Institute
University Of Wisconsin-madison
Year Funded
2016
FOA Number
Status
Complete
Project Number
Priority Area
  • Integrated Approaches
  • Theory & Data Analysis Tools
Summary

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.

Investigator
Sweedler, Jonathan V.
Institute
University Of Illinois At Urbana-champaign
Year Funded
2015
FOA Number
Status
Complete
Project Number
Priority Area
  • Cell Type
  • Circuit Diagrams
  • Monitor Neural Activity
  • Interventional Tools
Summary
Individual cell types contain specific combinations of chemical constituents that directly affect cell behavior. However, detailed knowledge of these constituents, as well as a precise method for identifying them, is currently lacking. Sweedler and colleagues will combine two methods for probing the chemical makeup of living tissue—mass spectrometry of individual cells, and stimulated Raman scattering microscopy (SRSM) from unlabeled tissue in brain slices. The combined analyses will be deployed in the dentate gyrus region of the hippocampus to identify the region’s many different cell types and chemical characteristics, and to investigate how this wealth of information relates to functions involved in memory formation.