Cognitive chimera states in human brain networks

TL;DR

This paper introduces a novel framework based on chimera states to understand how large-scale brain architecture influences cognitive function and variability in brain dynamics.

Contribution

It proposes a cognitively-informed, chimera-based approach to analyze personalized brain network models and their impact on cognitive system synchronization.

Findings

Identification of four groups of cognitive systems with distinct variability patterns

Demonstration of how regional stimulation affects synchronization across cognitive networks

Insights into the role of structural variability in brain dynamics

Abstract

The human brain is a complex dynamical system that gives rise to cognition through spatiotemporal patterns of coherent and incoherent activity between brain regions. As different regions dynamically interact to perform cognitive tasks, variable patterns of partial synchrony can be observed, forming chimera states. We propose that the emergence of such states plays a fundamental role in the cognitive organization of the brain, and present a novel cognitively-informed, chimera-based framework to explore how large-scale brain architecture affects brain dynamics and function. Using personalized brain network models, we systematically study how regional brain stimulation produces different patterns of synchronization across predefined cognitive systems. We then analyze these emergent patterns within our novel framework to understand the impact of subject-specific and region-specific structural variability on brain dynamics. Our results suggest a classification of cognitive systems into four groups with differing levels of subject and regional variability that reflect their different functional roles.