Brain resilience across the general cognitive ability distribution: Evidence from structural connectivity.
Brain connectomics
Brain resilience
Cognition
Network integrity
Journal
Brain structure & function
ISSN: 1863-2661
Titre abrégé: Brain Struct Funct
Pays: Germany
ID NLM: 101282001
Informations de publication
Date de publication:
Apr 2021
Apr 2021
Historique:
received:
04
04
2020
accepted:
30
12
2020
pubmed:
22
1
2021
medline:
3
11
2021
entrez:
21
1
2021
Statut:
ppublish
Résumé
Resting state functional connectivity research has shown that general cognitive ability (GCA) is associated with brain resilience to targeted and random attacks (TAs and RAs). However, it remains to be seen if the finding generalizes to structural connectivity. Furthermore, individuals showing performance levels at the very high area of the GCA distribution have not yet been analyzed in this regard. Here we study the relation between TAs and RAs to structural brain networks and GCA. Structural and diffusion-weighted MRI brain images were collected from 189 participants: 60 high cognitive ability (HCA) and 129 average cognitive ability (ACA) individuals. All participants completed a standardized fluid reasoning ability test and the results revealed an average HCA-ACA difference equivalent to 33 IQ points. Automated parcellation of cortical and subcortical nodes was combined with tractography to achieve an 82 × 82 connectivity matrix for each subject. Graph metrics were derived from the structural connectivity matrices. A simulation approach was used to evaluate the effects of recursively removing nodes according to their network centrality (TAs) versus eliminating nodes at random (RAs). HCA individuals showed greater network integrity at baseline and prior to network collapse than ACA individuals. These effects were more evident for TAs than RAs. The networks of HCA individuals were less degraded by the removal of nodes corresponding to more complex information processing stages of the PFIT network, and from removing nodes with larger empirically observed centrality values. Analyzed network features suggest quantitative instead of qualitative differences at different levels of the cognitive ability distribution.
Identifiants
pubmed: 33474577
doi: 10.1007/s00429-020-02213-4
pii: 10.1007/s00429-020-02213-4
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
845-859Subventions
Organisme : Ministerio de Economía, Industria y Competitividad, Gobierno de España
ID : PSI2017-82218-P
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