Well-being is associated with cortical thickness network topology of human brain.
Cortical thickness
MRI
Network centrality
Network efficiency
Well-being
Journal
Behavioral and brain functions : BBF
ISSN: 1744-9081
Titre abrégé: Behav Brain Funct
Pays: England
ID NLM: 101245751
Informations de publication
Date de publication:
25 Sep 2023
25 Sep 2023
Historique:
received:
01
04
2022
accepted:
18
09
2023
medline:
27
9
2023
pubmed:
26
9
2023
entrez:
25
9
2023
Statut:
epublish
Résumé
Living a happy and meaningful life is an eternal topic in positive psychology, which is crucial for individuals' physical and mental health as well as social functioning. Well-being can be subdivided into pleasure attainment related hedonic well-being or emotional well-being, and self-actualization related eudaimonic well-being or psychological well-being plus social well-being. Previous studies have mostly focused on human brain morphological and functional mechanisms underlying different dimensions of well-being, but no study explored brain network mechanisms of well-being, especially in terms of topological properties of human brain morphological similarity network. Therefore, in the study, we collected 65 datasets including magnetic resonance imaging (MRI) and well-being data, and constructed human brain morphological network based on morphological distribution similarity of cortical thickness to explore the correlations between topological properties including network efficiency and centrality and different dimensions of well-being. We found emotional well-being was negatively correlated with betweenness centrality in the visual network but positively correlated with eigenvector centrality in the precentral sulcus, while the total score of well-being was positively correlated with local efficiency in the posterior cingulate cortex of cortical thickness network. Our findings demonstrated that different dimensions of well-being corresponded to different cortical hierarchies: hedonic well-being was involved in more preliminary cognitive processing stages including perceptual and attentional information processing, while hedonic and eudaimonic well-being might share common morphological similarity network mechanisms in the subsequent advanced cognitive processing stages.
Sections du résumé
BACKGROUND
BACKGROUND
Living a happy and meaningful life is an eternal topic in positive psychology, which is crucial for individuals' physical and mental health as well as social functioning. Well-being can be subdivided into pleasure attainment related hedonic well-being or emotional well-being, and self-actualization related eudaimonic well-being or psychological well-being plus social well-being. Previous studies have mostly focused on human brain morphological and functional mechanisms underlying different dimensions of well-being, but no study explored brain network mechanisms of well-being, especially in terms of topological properties of human brain morphological similarity network.
METHODS
METHODS
Therefore, in the study, we collected 65 datasets including magnetic resonance imaging (MRI) and well-being data, and constructed human brain morphological network based on morphological distribution similarity of cortical thickness to explore the correlations between topological properties including network efficiency and centrality and different dimensions of well-being.
RESULTS
RESULTS
We found emotional well-being was negatively correlated with betweenness centrality in the visual network but positively correlated with eigenvector centrality in the precentral sulcus, while the total score of well-being was positively correlated with local efficiency in the posterior cingulate cortex of cortical thickness network.
CONCLUSIONS
CONCLUSIONS
Our findings demonstrated that different dimensions of well-being corresponded to different cortical hierarchies: hedonic well-being was involved in more preliminary cognitive processing stages including perceptual and attentional information processing, while hedonic and eudaimonic well-being might share common morphological similarity network mechanisms in the subsequent advanced cognitive processing stages.
Identifiants
pubmed: 37749598
doi: 10.1186/s12993-023-00219-6
pii: 10.1186/s12993-023-00219-6
pmc: PMC10521404
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
16Subventions
Organisme : National Natural Science Foundation of China
ID : 11674388
Informations de copyright
© 2023. BioMed Central Ltd.
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