The positive-negative mode link between brain connectivity, demographics and behaviour: a pre-registered replication of Smith
Human Connectome Project
adolescent brain cognitive development
connectomics
functional connectivity
network neuroscience
replication
Journal
Royal Society open science
ISSN: 2054-5703
Titre abrégé: R Soc Open Sci
Pays: England
ID NLM: 101647528
Informations de publication
Date de publication:
Feb 2022
Feb 2022
Historique:
received:
18
06
2020
accepted:
21
12
2021
entrez:
21
2
2022
pubmed:
22
2
2022
medline:
22
2
2022
Statut:
epublish
Résumé
In mental health research, it has proven difficult to find measures of brain function that provide reliable indicators of mental health and well-being, including susceptibility to mental health disorders. Recently, a family of data-driven analyses have provided such reliable measures when applied to large, population-level datasets. In the current pre-registered replication study, we show that the canonical correlation analysis (CCA) methods previously developed using resting-state magnetic resonance imaging functional connectivity and subject measures (SMs) of cognition and behaviour from healthy adults are also effective in measuring well-being (a 'positive-negative axis') in an independent developmental dataset. Our replication was successful in two out of three of our pre-registered criteria, such that a primary CCA mode's weights displayed a significant positive relationship and explained a significant amount of variance in both functional connectivity and SMs. The only criterion that was not successful was that compared to other modes the magnitude of variance explained by the primary CCA mode was smaller than predicted, a result that could indicate a developmental trajectory of a primary mode. This replication establishes a signature neurotypical relationship between connectivity and phenotype, opening new avenues of research in neuroscience with clear clinical applications.
Identifiants
pubmed: 35186306
doi: 10.1098/rsos.201090
pii: rsos201090
pmc: PMC8847886
doi:
Banques de données
figshare
['10.6084/m9.figshare.c.5798713']
Types de publication
Journal Article
Langues
eng
Pagination
201090Informations de copyright
© 2022 The Authors.
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