Mechanisms of distributed working memory in a large-scale network of macaque neocortex
Abstract
Neural activity underlying working memory is not a local phenomenon but distributed across multiple brain regions. To elucidate the circuit mechanism of such distributed activity, we developed an anatomically constrained computational model of large-scale macaque cortex. We found that mnemonic internal states may emerge from inter-areal reverberation, even in a regime where none of the isolated areas is capable of generating self-sustained activity. The mnemonic activity pattern along the cortical hierarchy indicates a transition in space, separating areas engaged in working memory and those which do not. 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, the role of prefrontal areas in controlling distributed attractors, and the resilience of distributed activity to lesions or inactivation. This work provides a theoretical framework for identifying large-scale brain mechanisms and computational principles of distributed cognitive processes.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Feb 24, 2022
- Source ID
- 10.7554/elife.72136
Entities
People
- Jorge F Mejias
- Xiao-Jing Wang
Organizations
- National Institutes of Health
- National Science Foundation
- New York University
- Office of Naval Research
- Simons Foundation
- University of Amsterdam