EFRI BEGIN OI: Biocomputing and learning with synthetic and biological oscillators on spatial architectures

NSF Award Search · 01002526DB NSF RESEARCH & RELATED ACTIVIT · $1,999,999 · view on nsf.gov ↗

Abstract

The human nervous system enables effortless focus on a single conversation in crowded and noisy environments, through mental filtering-out of the surrounding noise. This phenomenon, known as the Cocktail Party Problem (CPP) highlights the brain’s remarkable ability to focus attention, integrate sensory input, and enhance a specific auditory signal while suppressing all others in a way that no current machine can replicate. Emerging evidence suggests that the noise-filtering ability relies on ‘brain rhythms’ shaped by the structure of the brain. This award will support research inspired by auditory perception in the brain. The project is organized around three core thrusts: (1) developing mathematical models to describe the neural computations underlying this capability, (2) engineering neural systems with interfaces to stimulate and record neural behavior, and (3) creating a framework to examine the societal implications, ethical considerations, and public understanding of this research, aiming to foster trust and responsible innovation. This project could lay the foundations for future design of neural computing systems. This research seeks to develop both the mathematical foundations and technological platforms for computing using neural oscillations. The theoretical framework builds on recent advances in Bayesian inference and mean-field game theory to model core bio-computational processes – such as encoding, learning and inference – within structured neural substrates

Key facts

NSF award ID
2515342
Awardee
University of Illinois at Urbana-Champaign (IL)
SAM.gov UEI
Y8CWNJRCNN91
PI
Prashant G Mehta
Primary program
01002526DB NSF RESEARCH & RELATED ACTIVIT
All programs
Estimated total
$1,999,999
Funds obligated
$1,999,999
Transaction type
Standard Grant
Period
08/15/2025 → 07/31/2029