Project Grant 2601981
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $331,902 Project Grant to the Trustees of Boston University on August 15, 2023 under the Mathematical and Physical Sciences program (CFDA 47.049). The purpose of this 3-year grant is to develop rigorous mathematical analysis and theory for the training algorithms used in neural network models across various machine learning applications. The research will leverage stochastic analysis and weak convergence theory...
- The National Science Foundation Division of Molecular and Cellular Biosciences awarded the Trustees of Boston University $1,035,226 on August 1, 2026, under the Biological Sciences program (CFDA 47.074) to investigate how populations of neurons across multiple brain areas coordinate to mediate flexible decision-making—the process of combining sensory evidence and context to select appropriate actions toward behavioral goals. The research examines neural dynamics underlying perceptual...
- The Massachusetts Institute of Technology (MIT) received a $108,000 Project Grant award from the National Science Foundation Division of Computing and Communication Foundations to support collaboration research on probabilistic, geometric, and topological analysis of neural networks from theory to applications. The two-year award, issued on January 1, 2022 and set to conclude on December 31, 2024, will fund research under the Mathematical and Physical Sciences program (CFDA #47.049). This...
- The National Science Foundation Directorate for Mathematical and Physical Sciences awarded Brown University $270,000 on August 1, 2026, as a Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to develop a mathematical framework for recurrent threshold-linear networks (TLNs) capable of generating both static and complex dynamic patterns of activity. The project, titled "Sequential and Fusion Attractors as a Mechanism for Complex Rhythm Generation and Neural...
- This $266,538 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports collaborative research on the effects of connectivity architecture and distributed delays in brain network dynamics. The project aims to establish a quantitative framework that considers both spatial connectivity and temporal history of neural interactions, using networks of coupled equations with time delays. The research team, led by The Research...
- The National Science Foundation Division of Mathematical Sciences awarded the University of Washington $249,652 on September 15, 2026, to develop statistical machine learning tools and theory for inferring brain functional connectivity networks from neuronal spike train data. The project addresses new theoretical and methodological challenges in spectral-domain analysis of high-dimensional point processes derived from live neuronal recordings. Unlike existing time-domain approaches, the...
- This federal Project Grant award of $299,792.00 from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support research on multi-state bootstrap percolation on directed graphs as a framework for analyzing neuronal network activity and dynamics. The principal investigator will develop novel mathematical methods to study how neuronal activity spreads in networks, how it depends on network connectivity patterns, and identify key properties of...
- 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...
- The National Science Foundation Division of Mathematical Sciences awarded the Trustees of Boston University $250,000 on September 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to advance mathematical and computational understanding of quasi-periodic and quasi-crystalline patterns in partial differential equation models. The project develops new mathematical and numerical continuation techniques to characterize coherent structures—including fronts, defects, and...
- The National Science Foundation Directorate for Mathematical and Physical Sciences awarded the University of Massachusetts $300,000 on August 15, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop mathematical principles that make artificial intelligence systems more stable, reliable, and robust. The project establishes foundational theory to explain why successful AI algorithms work, identify conditions under which they fail, and guide their design for...
The National Science Foundation Division of Mathematical Sciences awarded $244,999 to the Trustees of Boston University on September 1, 2026, for theoretical research on stochastic dynamics of cortical neural networks under the Mathematical and Physical Sciences program (CFDA 47.049). The research develops statistical field theoretical frameworks linking neural and synaptic biology to collective network dynamics, using tools from statistical field theory applied to soft-threshold neuron models. The project studies nonlinear integrate-and-fire models fitted to large-scale public datasets and constructs network models of mouse cortical networks, exposing mean-field limits and approximations through graphical algorithms for fluctuation expansions. Results will be implemented in open-source software and aim to inform artificial intelligence and machine learning architectures inspired by biological networks. The work operates under the premise that biological neural networks function under strict resource constraints unlike energy-intensive machine learning systems, and that understanding how neuron and synapse biology shapes collective function has implications for treating neurological disease and engineering intelligent systems. Performance occurs in Boston, Massachusetts, with a period of performance through August 31, 2029. The project includes student training at the interface of neuroscience and mathematics.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $245.0k | 8/4/26 |