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A mechanistic model of connector hubs, modularity and cognition

Author

Listed:
  • Maxwell A. Bertolero

    (University of California
    University of Pennsylvania)

  • B. T. Thomas Yeo

    (National University of Singapore
    National University of Singapore)

  • Danielle S. Bassett

    (University of Pennsylvania
    University of Pennsylvania
    University of Pennsylvania
    University of Pennsylvania)

  • Mark D’Esposito

    (University of California)

Abstract

The human brain network is modular—consisting of communities of tightly interconnected nodes1. This network contains local hubs, which have many connections within their own communities, and connector hubs, which have connections diversely distributed across communities2,3. A mechanistic understanding of these hubs and how they support cognition has not been demonstrated. Here, we leveraged individual differences in hub connectivity and cognition. We show that a model of hub connectivity accurately predicts the cognitive performance of 476 individuals in 4 distinct tasks. Moreover, there is a general optimal network structure for cognitive performance—individuals with diversely connected hubs and consequent modular brain networks exhibit increased cognitive performance, regardless of the task. Critically, we find evidence consistent with a mechanistic model in which connector hubs tune the connectivity of their neighbours to be more modular while allowing for task appropriate information integration across communities, which increases global modularity and cognitive performance.

Suggested Citation

  • Maxwell A. Bertolero & B. T. Thomas Yeo & Danielle S. Bassett & Mark D’Esposito, 2018. "A mechanistic model of connector hubs, modularity and cognition," Nature Human Behaviour, Nature, vol. 2(10), pages 765-777, October.
    • Handle: RePEc:nat:nathum:v:2:y:2018:i:10:d:10.1038_s41562-018-0420-6
    DOI: 10.1038/s41562-018-0420-6
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    Cited by:

    1. Laura E. Suárez & Agoston Mihalik & Filip Milisav & Kenji Marshall & Mingze Li & Petra E. Vértes & Guillaume Lajoie & Bratislav Misic, 2024. "Connectome-based reservoir computing with the conn2res toolbox," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Jianzhong Chen & Angela Tam & Valeria Kebets & Csaba Orban & Leon Qi Rong Ooi & Christopher L. Asplund & Scott Marek & Nico U. F. Dosenbach & Simon B. Eickhoff & Danilo Bzdok & Avram J. Holmes & B. T., 2022. "Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    3. Alexander J Barnett & Walter Reilly & Halle R Dimsdale-Zucker & Eda Mizrak & Zachariah Reagh & Charan Ranganath, 2021. "Intrinsic connectivity reveals functionally distinct cortico-hippocampal networks in the human brain," PLOS Biology, Public Library of Science, vol. 19(6), pages 1-34, June.

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