Systems Neuroscience

Neural mechanisms and behavioral consequences of non-Gaussian likelihoods in sensorimotor learning

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. A critical gap therefore exists between the large amount of behavioral and neural data that has been collected during learning and a mathematical and biological understanding of the rules governing motor plasticity.

Beyond Diagnostic Classification of Autism: Neuroanatomical, Functional, and Behavioral Phenotypes

Project Summary Autism spectrum disorder (ASD) is a heterogeneous disorder characterized by repetitive and stereotyped be- havior and difficulties in communication and social interaction. It is now one of the most prevalent psychiatric disorders in childhood, but it is also a lifelong condition, adversely affecting an individual's social relationships, independence and employment well into adult.

Bayesian estimation of network connectivity and motifs

Abstract The overarching goal of this proposal is to learn how large groups of neurons interact in a network to perform computations that go beyond the individual ability of each cell. Our working hypothesis is that emergent behavior in neural networks results from their organization into a hierarchy of modular sub-networks or motifs, each performing simpler computations than the network as a whole.

Theories, Models and Methods for Analysis of Complex Data from the Brain

This FOA solicits new theories, computational models, and statistical methods to derive understanding of brain function from complex neuroscience data. Approaches could include the creation of new theories, ideas, and conceptual frameworks to organize/unify data and infer general principles of brain function; new computational models to develop testable hypotheses and design/drive experiments; and new mathematical and statistical methods to support or refute a stated hypothesis about brain function, and/or assist in detecting features in complex brain data.

BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain (R01 Clinical Trial Not Allowed)

This FOA solicits the development of theories, computational models, and analytical tools to derive understanding of brain function from complex neuroscience data. Proposed tools could include tools to integrate existing theories or formulate new theories; conceptual frameworks to organize or fuse data to infer general principles of brain function; multiscale/multiphysics models to generate new testable hypotheses to design/drive future experiments; new analytical methods to either support or refute a stated hypothesis about brain function..

BRAIN Initiative: Brain-Behavior Quantification and Synchronization Transformative and Integrative Models of Behavior at the Organismal Level (R34 Clinical Trial Not Allowed)

This R34 Funding Opportunity Announcement (FOA) seeks applications with limited scope proposing a set of planning activities that will lay the groundwork for a scientific project aimed at integrating complementary theories and methods to 1) develop, validate and apply cutting-edge tools and methods for minimally invasive, multi-dimensional, high-resolution measurement of behavior at the level of the organism, with synchronous capture of changes in the organisms social or physical environment; and/or 2) develop computational methods that allow for integration of multidimensional behavioral a

BRAIN Initiative: Targeted BRAIN Circuits Planning Projects TargetedBCPP (R34 Clinical Trials Not Allowed)

(Reissue of RFA-NS-18-014) This R34 FOA solicits applications that offer a limited scope of aims and an approach that will establish feasibility, validity, or other technically qualifying results that, if successful, would support, enable, and/or lay the groundwork for a potential, subsequent Targeted Brain Circuits Projects - TargetedBCP R01, as described in the companion FOA (RFA-NS-18-009). Applications should be exploratory research projects that use innovative, methodologically-integrated approaches to understand how circuit activity gives rise to mental experience and behavior.

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