A mechanistic model of connector hubs, modularity and cognition.

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TitleA mechanistic model of connector hubs, modularity and cognition.
Publication TypeJournal Article
Year of Publication2018
AuthorsBertolero, MA, Yeo, BTThomas, Bassett, DS, D'Esposito, M
JournalNat Hum Behav
Volume2
Issue10
Pagination765-777
Date Published2018 Oct
ISSN2397-3374
Abstract

The human brain network is modular-comprised of communities of tightly interconnected nodes. This network contains local hubs, which have many connections within their own communities, and connector hubs, which have connections diversely distributed across communities. 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 four 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 neighbors to be more modular while allowing for task appropriate information integration across communities, which increases global modularity and cognitive performance.

DOI10.1038/s41562-018-0420-6
Alternate JournalNat Hum Behav
PubMed ID30631825
PubMed Central IDPMC6322416
Grant ListR01 MH107235 / MH / NIMH NIH HHS / United States
R01 DC009209 / DC / NIDCD NIH HHS / United States
R21 MH106799 / MH / NIMH NIH HHS / United States
R01 HD086888 / HD / NICHD NIH HHS / United States
R01 NS079698 / NS / NINDS NIH HHS / United States
U54 MH091657 / MH / NIMH NIH HHS / United States
T32 MH106442 / MH / NIMH NIH HHS / United States
R01 MH107703 / MH / NIMH NIH HHS / United States