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

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

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. On the technological front, the project will engineer in vitro neural substrates that replicate cortical architectures guided by mathematical models derived from in vivo data. These 3D neural constructs will be integrated with electric, fluidic, and optical interfaces, enabling high-resolution access to neural dynamics allowing unprecedented insight into how oscillatory activity shapes learning and inference across network topologies. Taken together, the theoretical and technological components will provide a foundational understanding of design principles for next-generation 3D neural computing systems. Complementing this scientific work is an embedded ethical component that explores the broader societal implications of AI and biohybrid computing. This project will engage the public to explore the social, cultural, and ethical factors that influence the responsible development of these technologies. Ultimately the project aspires to deliver a comprehensive framework for ethical innovation – one that fosters public trust while supporting sustainable progress at the intersection of neuroscience, artificial intelligence, and society. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.