Project Grant 2602201

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 Binding in Recurrent Networks," addresses how brains generate complex behaviors using stable structure and limited resources—a contrast to modern artificial intelligence systems that rely on computationally expensive, large networks difficult to interpret and often task-specific. The research applies a modular approach in which simple building blocks can be mixed and matched to obtain complex functions, with insights applied to the design of biologically inspired, cheaper-to-implement hardware easier to interpret. The project spans the interface of neuroscience, mathematics, and engineering with impacts for biotechnology and robotics. Work is performed at Providence, Rhode Island, with a performance period from August 1, 2026, through July 31, 2029. The project includes educational components involving undergraduate and graduate students from mathematics, neuroscience, computer science, and engineering disciplines to prepare an interdisciplinary skilled workforce for advanced careers in industry and academia.