Pattern learning reveals brain asymmetry to be linked to socioeconomic status.
brain lateralization
hemispheric asymmetry
machine learning
multi-output pattern learning
population neuroscience
socioeconomic status
Journal
Cerebral cortex communications
ISSN: 2632-7376
Titre abrégé: Cereb Cortex Commun
Pays: United States
ID NLM: 101767128
Informations de publication
Date de publication:
2022
2022
Historique:
received:
25
10
2021
revised:
13
05
2022
accepted:
15
05
2022
entrez:
15
6
2022
pubmed:
16
6
2022
medline:
16
6
2022
Statut:
epublish
Résumé
Socioeconomic status (SES) anchors individuals in their social network layers. Our embedding in the societal fabric resonates with habitus, world view, opportunity, and health disparity. It remains obscure how distinct facets of SES are reflected in the architecture of the central nervous system. Here, we capitalized on multivariate multi-output learning algorithms to explore possible imprints of SES in gray and white matter structure in the wider population (
Identifiants
pubmed: 35702547
doi: 10.1093/texcom/tgac020
pii: tgac020
pmc: PMC9188625
doi:
Types de publication
Journal Article
Langues
eng
Pagination
tgac020Subventions
Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press.
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