Mechanisms of distributed working memory in a large-scale network of macaque neocortex

Abstract

To elucidate the circuit mechanism of persistent neural activity underlying working memory that is distributed across multiple brain regions, we developed an anatomically constrained computational model of large-scale macaque cortex. We found that persistent activity may emerge from inter-areal reverberation, even in a regime where none of the isolated areas is capable of generating persistent activity. The persistent activity pattern along the cortical hierarchy indicates a robust bifurcation in space, characterized by a few association areas near dynamical criticality. A host of spatially distinct attractor states is found, potentially subserving various internal processes. The model yields testable predictions including the idea of counterstream inhibitory bias, and suggests experiments to differentiate local versus distributed mechanisms. Simulated lesion or optogenetic inactivation revealed that distributed activity patterns are resilient while dependent on a structural core. This work provides a theoretical framework for identifying large-scale brain mechanisms and computational principles of distributed cognitive processes.