Controllability of structural brain networks

Shi Gu, Fabio Pasqualetti, Matthew Cieslak, Qawi K. Telesford, Alfred B. Yu, Ari E. Kahn, John D. Medaglia, Jean M. Vettel, Michael B. Miller, Scott T. Grafton and Danielle S. Bassett ()
Additional contact information
Shi Gu: University of Pennsylvania
Fabio Pasqualetti: University of California
Matthew Cieslak: University of California
Qawi K. Telesford: University of Pennsylvania
Alfred B. Yu: Translational Neuroscience Branch, Army Research Laboratory
Ari E. Kahn: University of Pennsylvania
John D. Medaglia: University of Pennsylvania
Jean M. Vettel: University of California
Michael B. Miller: University of California
Scott T. Grafton: University of California
Danielle S. Bassett: University of Pennsylvania

Nature Communications, 2015, vol. 6, issue 1, 1-10

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.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms9414

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DOI: 10.1038/ncomms9414

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