Controllability of structural brain networks

Shi Gu(University of the Sciences), Fabio Pasqualetti(University of California, Riverside), Matthew Cieslak(University of California, Santa Barbara), Qawi K. Telesford(DEVCOM Army Research Laboratory), Alfred B. Yu(DEVCOM Army Research Laboratory), Ari E. Kahn(University of Pennsylvania), John D. Medaglia(University of Pennsylvania), Jean M. Vettel(University of California, Santa Barbara), Michael B. Miller(University of California, Santa Barbara), Scott T. Grafton(University of California, Santa Barbara), Danielle S. Bassett(University of Pennsylvania)
Nature Communications
October 1, 2015
Cited by 964Open Access
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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.


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