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Controllability of structural brain networks.
Gu, Shi; Pasqualetti, Fabio; Cieslak, Matthew; Telesford, Qawi K; Yu, Alfred B; Kahn, Ari E; Medaglia, John D; Vettel, Jean M; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S.
Affiliation
  • Gu S; Department of Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
  • Pasqualetti F; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
  • Cieslak M; Department of Mechanical Engineering, University of California, Riverside, California 92521, USA.
  • Telesford QK; Department of Psychological and Brain Sciences, University of California, Santa Barbara, California 93106, USA.
  • Yu AB; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
  • Kahn AE; Translational Neuroscience Branch, Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, Maryland 20783, USA.
  • Medaglia JD; Translational Neuroscience Branch, Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, Maryland 20783, USA.
  • Vettel JM; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
  • Miller MB; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
  • Grafton ST; Department of Psychological and Brain Sciences, University of California, Santa Barbara, California 93106, USA.
  • Bassett DS; Translational Neuroscience Branch, Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, Maryland 20783, USA.
Nat Commun ; 6: 8414, 2015 Oct 01.
Article de En | MEDLINE | ID: mdl-26423222
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.
Sujet(s)

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Encéphale / Cognition / Réseau nerveux Limites: Adult / Female / Humans / Male Langue: En Journal: Nat Commun Sujet du journal: BIOLOGIA / CIENCIA Année: 2015 Type de document: Article Pays d'affiliation: États-Unis d'Amérique

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Encéphale / Cognition / Réseau nerveux Limites: Adult / Female / Humans / Male Langue: En Journal: Nat Commun Sujet du journal: BIOLOGIA / CIENCIA Année: 2015 Type de document: Article Pays d'affiliation: États-Unis d'Amérique