The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Function

TL;DR

This study reveals that the human brain dynamically switches between segregated and integrated network states, with the integrated state enhancing cognitive performance and linked to neuromodulatory activity.

Contribution

It introduces a time-resolved network analysis approach to demonstrate brain state transitions and their impact on cognition and neuromodulation.

Findings

Brain alternates between segregation and integration states.

Integrated state correlates with improved cognitive performance.

Pupil dilation suggests neuromodulatory influence on state transitions.

Abstract

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions, however it is unclear how this mechanism manifests over time. In this study, we use time-resolved network analysis of functional magnetic resonance imaging data to demonstrate that the human brain traverses between two functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. The integrated state enables faster and more accurate performance on a cognitive task, and is associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Our data confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.