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Functional brain network community structure in childhood: Unfinished territories and fuzzy boundaries

Authors :
Ursula A. Tooley
Danielle S. Bassett
Allyson P. Mackey
Source :
NeuroImage, Vol 247, Iss , Pp 118843- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Adult cortex is organized into distributed functional communities. Yet, little is known about community architecture of children’s brains. Here, we uncovered the community structure of cortex in childhood using fMRI data from 670 children aged 9–11 years (48% female, replication sample n=544, 56% female) from the Adolescent Brain and Cognitive Development study. We first applied a data-driven community detection approach to cluster cortical regions into communities, then employed a generative model-based approach called the weighted stochastic block model to further probe community interactions. Children showed similar community structure to adults, as defined by Yeo and colleagues in 2011, in early-developing sensory and motor communities, but differences emerged in transmodal areas. Children have more cortical territory in the limbic community, which is involved in emotion processing, than adults. Regions in association cortex interact more flexibly across communities, creating uncertainty for the model-based assignment algorithm, and perhaps reflecting cortical boundaries that are not yet solidified. Uncertainty was highest for cingulo-opercular areas involved in flexible deployment of cognitive control. Activation and deactivation patterns during a working memory task showed that both the data-driven approach and a set of adult communities statistically capture functional organization in middle childhood. Collectively, our findings suggest that community boundaries are not solidified by middle childhood.

Details

Language :
English
ISSN :
10959572
Volume :
247
Issue :
118843-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.877cead81dd14ecfabeefc3e57647000
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2021.118843