Controlling brain dynamics: Landscape and transition path for working memory

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. A fundamental aspect of brain science is understanding our brain and interacting with it. Here, using a large-scale model of macaque brain, we investigate the stochastic dynamical mechanism of working memory. The alteration in landscape and brain state switching in response to task demands governs the working memory function. The kinetic transition path demonstrates that the hierarchical structure determines the direction of information flow. Significantly, we propose a landscape control approach to manipulate the relative stability and transition of brain states by identifying key nodes and edges in brain network, to improve the working memory performance. Our findings offer new way to comprehend dynamic mechanism of cognitive function and promote the development of therapeutic strategies for brain disorders.

Automated summary

By studying a large-scale macaque model, we quantified the energy landscape of working memory and found that brain-wide state switching and landscape change are crucial for working memory function. The kinetic transition path reveals that information flow follows a hierarchical structure. We propose a landscape control approach to manipulate brain state transition by modulating external stimulation or inter-areal connectivity, highlighting the important 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 help develop therapeutic strategies for brain disorders.