Xiao Jing Wang
Swartz Center for Theoretical Neuroscience, New York University

I will introduce the concept of “cognitive-type” neural circuits, in contrast to sensory or motor systems, that are capable of decision-making and working memory. These circuits are nonlinear stochastic dynamical systems characterized by a duality of slow transients and attractor dynamics.
Our work revealed a hierarchy of timescales across the primate cortex, which is mathematically formulated as a problem of spatial localization of eigenmodes with diverse timescales, in spite of dense recurrent connections. This finding challenges conventional graph theoretical analysis, and suggests a mechanism for the emergence of new functions in different parts of the cortex.