Controllability of structural brain networks

TLDR

Cognitive function arises from dynamic interactions among large‑scale neural circuits, yet the fundamental principles governing these processes remain unclear. The study aims to explain how the brain transitions between cognitive states using the network organization of white‑matter microstructure. The authors employ control and network theory tools to model these transitions. Densely connected default‑mode areas enable easy state transitions, weakly connected cognitive‑control areas enable difficult transitions, boundary areas in attentional control systems integrate or segregate cognitive systems, and overall structural network differences dictate distinct roles in controlling brain network trajectories.

Abstract

Abstract Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these dynamic network processes have remained elusive. Here we use tools from control and network theories 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 cognitive circuits dictate their distinct roles in controlling trajectories of brain network function.