Project Grant 2242568
- This Project Grant award of $503,740 from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program supports the development of new probabilistic models and scalable machine learning techniques for analyzing complex spatiotemporal data, with a focus on applications to mapping dynamic brain connectivity. The principal investigator at Stanford University will create transformative tools for modeling high-dimensional spatiotemporal datasets, addressing...
- This National Science Foundation (NSF) Project Grant award, under the STEM Education (CFDA 47.076) program, provides $150,000 in funding to Lehigh University for a collaborative research project titled "DYNAMIC BRAIN GRAPH MINING - MAPPING THE CONNECTIONS IN HUMAN BRAINS AS NETWORKED SYSTEMS." The project aims to develop new methods for modeling the dynamics of brain graphs derived from neuroimaging data, in order to generate accurate, interpretable, and fair predictions about...
- This $375,000 Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports research to advance Bayesian inference methods for the analysis of complex human data. The project, conducted by Rensselaer Polytechnic Institute, will develop an efficient amortized Bayesian inference framework that enables researchers across the social and behavioral sciences to quickly fit, criticize, and adapt complex computational models. The...
- The University of Pittsburgh was awarded a $150,000 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049) to develop new statistical inference tools and theories for analyzing data with network dependency. Specifically, the award will support modeling and inference research for data exhibiting complex interpersonal dependency characterized by networks, with a focus on developing...
- This National Science Foundation project grant of $625,000 will fund research into the brain network mechanisms underlying task-general cognition and intelligent human behavior from September 2022 to August 2025. Under the federal Social, Behavioral, and Economic Sciences program (CFDA 47.075), Rutgers University, Newark will investigate how dynamic activity flows within cognitive control networks implement intelligent goal-directed behavior across diverse tasks. Researchers will utilize brain...
- This National Science Foundation (NSF) Project Grant under the Social, Behavioral, and Economic Sciences program (CFDA 47.075) awarded Northeastern University $532,152 on May 1, 2025 to conduct research on the neurocognitive development of learning in adolescents. The project aims to investigate the cognitive and brain mechanisms related to learning from experience, and how these change from childhood to adolescence and young adulthood. Using behavioral, computational, and neuroimaging...
- This $425,875 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE, CFDA 47.070) program. The award was granted to The Leland Stanford Junior University (Stanford University) to develop new computational and statistical methods to analyze high-dimensional neural recording and behavioral video data. The goal is to better understand how the brain produces natural behavior by linking brain activity to...
- This federal Project Grant award of $301,800.00 from the National Science Foundation's Social, Behavioral, and Economic Sciences program (CFDA 47.075) supports a research project led by Yale University to study the neural mechanisms of object cognition using multilevel computational modeling. The overarching hypothesis is that the brain implements object cognition by building and manipulating generative models of physical scenes, their dynamics, and sensory inputs. The project aims to develop...
- This National Science Foundation Project Grant of $220,000 supports research into statistical modeling methods for large, complex datasets. Funded under the Mathematical and Physical Sciences program (CFDA 47.049), the University of California, San Francisco will develop new Bayesian regression techniques using random data compression matrices. These approaches aim to enable efficient, scalable inference and prediction from high-dimensional biomedical data sources like brain imaging, genetics,...
- This Project Grant award, provided by the National Science Foundation's Office of Multidisciplinary Activities under CFDA Program 47.075 - Social, Behavioral, and Economic Sciences, supports an early-career scientist's postdoctoral fellowship to study how childhood experiences shape brain development during adolescence. The $160,000 award, effective from September 1, 2025 to August 31, 2027, will fund research to characterize the links between childhood environment and cortical...
This Project Grant from the National Science Foundation Division of Social and Economic Science, under the Social, Behavioral, and Economic Sciences federal grant program (CFDA 47.075), provides $275,112 to the University of Pittsburgh for the project "Bayesian Inference of Whole-Brain Directed Networks using Neuroimaging Data." The project will develop new statistical models and computationally efficient algorithms to analyze functional magnetic resonance imaging (fMRI) data to better understand functional brain organization, changes during development, and relationships between brain and behavior in populations. Open-source software implementing the new statistical tools will be made publicly available. The investigator will apply the methods to neuroimaging and behavioral data from multiple subjects to examine variation in functional organization and its relationship to human behavior across populations. Findings aim to enhance understanding of the brain, human behavior, and risks for mental health challenges. The period of performance is May 1, 2023 through April 30, 2026.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $275.1k | 3/6/23 |