Optimal trajectories of brain state transitions

Shi Gu, Richard F. Betzel, Marcelo G. Mattar, Matthew Cieslak, Philip R. Delio, Scott T. Grafton, Fabio Pasqualetti, Danielle S. Bassett

Research output: Contribution to journalArticlepeer-review


The complexity of neural dynamics stems in part from the complexity of the underlying anatomy. Yet how white matter structure constrains how the brain transitions from one cognitive state to another remains unknown. Here we address this question by drawing on recent advances in network control theory to model the underlying mechanisms of brain state transitions as elicited by the collective control of region sets. We find that previously identified attention and executive control systems are poised to affect a broad array of state transitions that cannot easily be classified by traditional engineering-based notions of control. This theoretical versatility comes with a vulnerability to injury. In patients with mild traumatic brain injury, we observe a loss of specificity in putative control processes, suggesting greater susceptibility to neurophysiological noise. These results offer fundamental insights into the mechanisms driving brain state transitions in healthy cognition and their alteration following injury.

Original languageEnglish (US)
Pages (from-to)305-317
Number of pages13
StatePublished - Mar 1 2017


  • Cognitive control
  • Control theory
  • Diffusion imaging
  • Network neuroscience
  • Traumatic brain injury

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience


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