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Nat Commun. 2015 Oct 1;6:8414. doi: 10.1038/ncomms9414.

Controllability of structural brain networks.

Author information

  • 1Department of Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
  • 2Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
  • 3Department of Mechanical Engineering, University of California, Riverside, California 92521, USA.
  • 4Department of Psychological and Brain Sciences, University of California, Santa Barbara, California 93106, USA.
  • 5Translational Neuroscience Branch, Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, Maryland 20783, USA.
  • 6Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.


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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