Dynamics and computation in spatially resolved biological neural networks

Speaker's Name: Gabriel Benigno
Speaker's Affiliation: New York University
Speaker's Research Theme(s): CMMB,
Abstract:
Biological neural networks are inherently structured, with connectivity patterns and distance-dependent time delays that shape how information is processed across space and time in the brain. This structure is evident in experimental recordings, where coordinated population activity often manifests as traveling waves and other organized spatiotemporal patterns. In this talk, I will show how such dynamics play an essential role in prediction, communication, and computation in the cerebral cortex. Drawing on spatially resolved electrophysiological data in non-human primates, I will demonstrate evidence for wave-like propagation and structured spatiotemporal dynamics. I will then introduce computational models and analytical frameworks that reveal how spatial organization and distance-dependent delays foster pattern formation, enable information transfer, and support the generation of complex yet structured stochastic processes. Together, these results highlight how spatially structured dynamics provide a general resource for computation in neural circuits.

Venue: Online
Online Conference Link: https://teams.microsoft.com/meet/31519940113867?p=LDns0jPXmS5uJnBh6K