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Controlling brain dynamics: Landscape and transition path for working memory.

Authors :
Leijun Ye
Jianfeng Feng
Chunhe Li
Source :
PLoS Computational Biology, Vol 19, Iss 9, p e1011446 (2023)
Publication Year :
2023
Publisher :
Public Library of Science (PLoS), 2023.

Abstract

Understanding the underlying dynamical mechanisms of the brain and controlling it is a crucial issue in brain science. The energy landscape and transition path approach provides a possible route to address these challenges. Here, taking working memory as an example, we quantified its landscape based on a large-scale macaque model. The working memory function is governed by the change of landscape and brain-wide state switching in response to the task demands. The kinetic transition path reveals that information flow follows the direction of hierarchical structure. Importantly, we propose a landscape control approach to manipulate brain state transition by modulating external stimulation or inter-areal connectivity, demonstrating the crucial roles of associative areas, especially prefrontal and parietal cortical areas in working memory performance. Our findings provide new insights into the dynamical mechanism of cognitive function, and the landscape control approach helps to develop therapeutic strategies for brain disorders.

Subjects

Subjects :
Biology (General)
QH301-705.5

Details

Language :
English
ISSN :
1553734X and 15537358
Volume :
19
Issue :
9
Database :
Directory of Open Access Journals
Journal :
PLoS Computational Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.93dcac626f424e1dbcd2b392b92324a9
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pcbi.1011446&type=printable