Controllability of Brain Networks

TL;DR

This paper uses network control theory to explain how brain structural networks facilitate transitions between cognitive states, highlighting the roles of different brain regions in controlling brain dynamics.

Contribution

It introduces a novel application of network control theory to brain networks, revealing how structural connectivity influences cognitive state transitions.

Findings

Densely connected default mode areas enable easy state transitions.

Weakly connected control areas facilitate difficult state transitions.

Boundary regions support integration and segregation of cognitive systems.

Abstract

Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behavior. Fundamental principles constraining these dynamic network processes have remained elusive. Here we use network control theory to offer a mechanistic explanation for how the brain moves between cognitive states drawn from the network organization of white matter microstructure. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily-reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. Our results suggest that structural network differences between the cognitive circuits dictate their distinct roles in controlling dynamic trajectories of brain network function.