This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program will support research into the neuroscientific mechanisms of visual perception and cognition. The primary awardee, The Leland Stanford Junior University, will use an innovative "inception loop" technique combining multi-neuronal recordings and deep learning models to systematically characterize the neural tuning and receptive field...
This $300,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research at the University of Pittsburgh to develop new analytical tools and computational models to understand how the brain selectively processes relevant information and coordinates information flow across brain regions. The project aims to integrate existing datasets on large-scale neural activity and anatomical connectivity...
This Project Grant award from the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) to The Salk Institute for Biological Studies will provide $376,738 to study the low-dimensional structure and dynamics of neural activity in the brain. The Principal Investigator will analyze how neural population activity patterns, described as curved and expanding manifolds, change with learning. They will develop novel manifold learning methods and generalize classic results on the...
This $329,099 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant aims to develop new computational models to uncover the functional architecture of the brain and its role in enabling complex behaviors like navigation and decision-making. Specifically, the project will: Identify the brain systems underlying navigation in zebrafish larvae using advanced optical imaging...
This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program provides $599,986 to Stanford University for research titled "Machine Learning with Behavioral and Social Data." The five-year award beginning in August 2022 will support the development of new machine learning algorithms that model human decision-making descriptively based on behavioral data. The researcher aims to build on recent advances in modeling choices as driven by...
The National Science Foundation (NSF) awarded a $225,000 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to The Leland Stanford Junior University. The 3-year grant, effective July 1, 2024, aims to gain a deeper theoretical understanding of the statistical properties of neural networks, which have revolutionized science and engineering. Key research directions include studying the distinguishing features of deep neural networks compared to classical statistical...
This Project Grant award for $370,687 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a multiscale modeling framework to analyze brain structure and function, with a focus on understanding atypical neural activity in autism. The project aims to: 1) implement a multiscale forward model integrating cellular mechanisms and whole-brain dynamics using spiking neural networks and neural masses, 2)...
This Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports research to develop soft, conformable neural interface devices capable of monitoring brain activity as animals mature and develop complex cognitive abilities. The $283,596 award, with a period of performance from October 1, 2024 to November 30, 2026, will enable researchers at the University of California, Irvine to use...
This Project Grant award for $438,719.00, provided by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070), will support research to develop theoretical methods for analyzing large-scale brain connectivity datasets, or "connectomes." The research aims to identify and model sensorimotor pathways in whole-brain connectomes, which could inform models of brain signaling and intelligent behavior. Specifically,...
The National Science Foundation's Division of Information and Intelligent Systems awarded $454,115 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to Stanford University. The three-year Project Grant will support research to accelerate machine learning through the development of automated methods to clean data, reduce feature dimensionality, and recommend machine learning models using low-dimensional latent vectors. Principal Investigator will...