Optimal Control of Excitable Systems Near Criticality

Explore optimal control of excitable systems near criticality in this comprehensive talk from the Physical Review Journal Club. Delve into the research of Daniel B. Larremore and Juan G. Restrepo from the University of Colorado, Boulder, as they discuss their Physical Review Research paper. Discover how they studied a network of binary neurons to understand controlling neural activity fluctuations. Learn about the relationship between control efficacy, proximity to criticality, and network structural properties. Examine their findings on optimal control near criticality and its implications for networks with heterogeneous degree distributions. Gain insights into why the noisiest dynamical regime may also be the easiest to control. Follow the presentation of results and engage with the live question-and-answer session moderated by Raissa D'Souza. Cover topics including motivation, criticality, model control schemes, linear equations, branching functions, degree distributions, conclusions, experimental questions, heterogeneity, stochasticity, and control of selective nodes.