Mapping the structure-function relationship along macroscale gradients in the human brain.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
16 Aug 2024
16 Aug 2024
Historique:
received:
03
11
2023
accepted:
05
08
2024
medline:
17
8
2024
pubmed:
17
8
2024
entrez:
16
8
2024
Statut:
epublish
Résumé
Functional coactivation between human brain regions is partly explained by white matter connections; however, how the structure-function relationship varies by function remains unclear. Here, we reference large data repositories to compute maps of structure-function correspondence across hundreds of specific functions and brain regions. We use natural language processing to accurately predict structure-function correspondence for specific functions and to identify macroscale gradients across the brain that correlate with structure-function correspondence as well as cortical thickness. Our findings suggest structure-function correspondence unfolds along a sensory-fugal organizational axis, with higher correspondence in primary sensory and motor cortex for perceptual and motor functions, and lower correspondence in association cortex for cognitive functions. Our study bridges neuroscience and natural language to describe how structure-function coupling varies by region and function in the brain, offering insight into the diversity and evolution of neural network properties.
Identifiants
pubmed: 39152127
doi: 10.1038/s41467-024-51395-6
pii: 10.1038/s41467-024-51395-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
7063Subventions
Organisme : U.S. Department of Health & Human Services | NIH | Center for Information Technology (Center for Information Technology, National Institutes of Health)
ID : NIH RO1 NS109062
Organisme : U.S. Department of Health & Human Services | NIH | Center for Information Technology (Center for Information Technology, National Institutes of Health)
ID : NIH RO1 NS109062
Informations de copyright
© 2024. The Author(s).
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