PROJECT SUMMARY/ABSTRACT
Stroke is a disease of epidemiological proportions in the industrialized world and a leading cause of long-term
disabilities. One third of stroke patients maintain long-term motor deficits severe enough to be disabling,
despite rehabilitative efforts.
Funded Awards
The National Institutes of Health (NIH) BRAIN Initiative funds a wide-variety of research: toolmakers, trainees, individual labs testing new hypotheses, and large, team-based efforts aiming to catalyze neuroscience inquiry forward. Explore NIH BRAIN Initiative funded awards listed below. Click on the project title to learn more about it within NIH RePORTER.
To see more NIH-funded awards and associated publications, please visit the NIH RePORTER.
Title
Investigator(s)
Institution
Fiscal Year
Funding Opportunity #
Project #
TitleDeep cerebellar electrical stimulation for post-stroke motor recovery
Investigator
Kenneth B Baker, Andre Guelman Machado
Institute
cleveland clinic lerner com-cwru
Fiscal Year
Funding Opportunities Number
Project Number
TitleDiagnosis of Alzheimer's Disease Using Dynamic High-Order Brain Networks
Investigator
Dinggang Shen, Pew-Thian Yap
Institute
univ of north carolina chapel hill
Fiscal Year
Funding Opportunities Number
Project Number
Diagnosis of Alzheimer's Disease Using Dynamic High-
Order Brain Networks
Abstract
Alzheimer's disease (AD) is the most common form of dementia with no known disease-modifying treatment.
Current clinical diagnosis and monitoring of the disease are primarily based on subjective neuropsychological
and
TitleEFFECTIVE CONNECTIVITY IN BRAIN NETWORKS: Discovering Latent Structure, Network Complexity and Recurrence.
Investigator
Stephen José Hanson
Institute
rutgers the state univ of nj newark
Fiscal Year
Funding Opportunities Number
Project Number
Principal investigator/Program Director (Last, first, middle): Hanson, Stephen, José RFA-EB-15-006
Project Summary/Abstract
Since the earliest days of neuroscience research, core methods have focused on matching specific functions
to local brain structure and neural activity.
TitleEmbedded Ensemble Encoding
Investigator
Srdjan D Antic, William W Lytton
Institute
suny downstate medical center
Fiscal Year
Funding Opportunities Number
Project Number
Abstract
We are developing a novel embedded-ensemble encoding (EEE) theory for mammalian neocortex to unify data from
cell and network experiments, and to infer general principles of how information is processed in the brain.
TitleEmergent dynamics from network connectivity: a minimal model
Investigator
Carina Curto
Institute
pennsylvania state university, the
Fiscal Year
Funding Opportunities Number
Project Number
Project Summary
Even in the absence of changing sensory inputs, many networks in the brain exhibit emer-
gent dynamics: that is, they display patterns of neural activity that are shaped by the intrinsic
structure of the network, rather than modulated by an external input.
TitleFiltered Point Process Inference Framework for Modeling Neural Data
Investigator
Emery N Brown
Institute
massachusetts general hospital
Fiscal Year
Funding Opportunities Number
Project Number
ABSTRACT
Neuronal spike-trains and various other signals in the central nervous system have a discrete,
impulsive nature that is well characterized with point process statistical models.
TitleGraph theoretical analysis of the effect of brain tumors on functional MRI networks
Investigator
Andrei I Holodny, Hernan Makse
Institute
city college of new york
Fiscal Year
Funding Opportunities Number
Project Number
Project Summary/Abstract:
The broad, long-term objective of this grant is to advance a graph theoretical framework to identify core-nodes
in a Brain Network of Networks to develop a software tool that will allow end-users from the broad
neuroscience community to identify and analyze the most influen
TitleHuman Neocortical Neurosolver
Investigator
Matti Hamalainen, Michael L Hines, Stephanie Ruggiano Jones
Institute
brown university
Fiscal Year
Funding Opportunities Number
Project Number
Abstract
The field of neuroscience is experiencing unprecedented growth in the ability to record from and manipulate
brain circuits in humans and in animal models. MEG/EEG are the leading methods to non-invasively record
human neural dynamics with millisecond temporal resolution.
TitleLarge-scale Network Modeling for Brain Dynamics: Statistical Learning and Optimization
Investigator
Xi Luo
Institute
brown university
Fiscal Year
Funding Opportunities Number
Project Number
Summary
The human brain is a large, well-connected, and dynamic network.
TitleLearning spatio-temporal statistics from the environment in recurrent networks
Investigator
Nicolas Brunel, Harel Zeev Shouval
Institute
university of texas hlth sci ctr houston
Fiscal Year
Funding Opportunities Number
Project Number
Project Summary Abstract
Learning new tasks and exposure to new environments lead to changes in the dynamics of brain circuits, as
observed in various recent experiments.
TitleManifold-valued statistical models for longitudinal morphometic analysis in preclinical Alzheimer's disease (AD)
Investigator
Sterling C Johnson, Vikas Singh
Institute
university of wisconsin-madison
Fiscal Year
Funding Opportunities Number
Project Number
Project Summary
The ability to quantitatively characterize incipient Alzheimer's disease (AD) pathology in its preclinical stage is
a critical step for early interventions involving disease modifying therapy and for designing efficient clinical trials
to test therapy efficacy.
TitleMultimodal modeling framework for fusing structural and functional connectome data
Investigator
Srikantan S. Nagarajan, Ashish Raj
Institute
weill medical coll of cornell univ
Fiscal Year
Funding Opportunities Number
Project Number
PROJECT SUMMARY / ABSTRACT
Project Summary
A key goal of computational neuroscience is to discover how the brain’s structural organization produces its
functional behavior, and how impairment of the former causes dysfunction and disease.
TitleNetwork Connectivity Modeling of Heterogeneous Brain Data to Examine Ensembles of Activity Across Two Levels of Dimensionality
Investigator
Kathleen Gates
Institute
univ of north carolina chapel hill
Fiscal Year
Funding Opportunities Number
Project Number
Project Summary/Abstract
Network methods have emerged as some of the most useful approaches for analyzing functional MRI
data. While great advancements have been made in these methods, limitations hamper the progress fMRI
researchers can make in better understanding brain processes.
TitleNeural mechanisms and behavioral consequences of non-Gaussian likelihoods in sensorimotor learning
Investigator
Ilya M. Nemenman, Samuel Sober
Institute
emory university
Fiscal Year
Funding Opportunities Number
Project Number
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 understanding of both the computational basis
of learning and its implementation by the brain is still rudimentary.
TitleNext-Generation Calcium Imaging Analysis Methods
Investigator
Liam M Paninski
Institute
columbia univ new york morningside
Fiscal Year
Funding Opportunities Number
Project Number
Project Summary
Calcium imaging methods allow us to record the simultaneous activity of many neurons with single-cell
resolution; these methods are therefore a critical enabling tool for the BRAIN initiative and in neuroscience
more broadly.
TitleNoninvasive Biomarkers to Advance Emerging DBS Electrode Technologies in Parkinson's Disease
Investigator
Harrison Carroll Walker
Institute
university of alabama at birmingham
Fiscal Year
Funding Opportunities Number
Project Number
ABSTRACT
It is easy to underestimate the importance of normal movement in daily life, until that ability is altered or taken
away by disease.
TitleNovel Bayesian linear dynamical systems-based methods for discovering human brain circuit dynamics in health and disease
Investigator
Vinod Menon
Institute
stanford university
Fiscal Year
Funding Opportunities Number
Project Number
Project Summary/Abstract
Understanding how the human brain produces cognition ultimately depends on precise quantitative
characterization of context-dependent dynamic functional networks (DFN) that transiently link distributed
brain regions.
TitleShort Course in Adaptive Neurotechnologies
Investigator
Gerwin Schalk, Jonathan Rickel Wolpaw
Institute
wadsworth center
Fiscal Year
Funding Opportunities Number
Project Number
DESCRIPTION (provided by applicant): Neurological disorders affect many millions of people in the United States and throughout the world.
TitleToward a Theory for Macroscopic Neural Computation Based on Laplace Transform
Investigator
Marc W Howard
Institute
boston university (charles river campus)
Fiscal Year
Funding Opportunities Number
Project Number
PROJECT SUMMARY/ABSTRACT
The Weber-Fechner law is perhaps the oldest quantitative relationship in psychology.
TitleBerkeley Course on Mining and Modeling of Neuroscience Data
Investigator
Friedrich T Sommer
Institute
university of california berkeley
Fiscal Year
Funding Opportunities Number
Project Number
DESCRIPTION (provided by applicant): This proposal is to administer and further develop a successfully established two-week summer training course titled "Mining and Modeling of Neuroscience Data" which is held at UC Berkeley.