Unveiling whole-brain dynamics in normal aging through Hidden Markov Models.
Hidden Markov Models
brain states
dynamic functional connectivity
healthy aging
resting state networks
Journal
Human brain mapping
ISSN: 1097-0193
Titre abrégé: Hum Brain Mapp
Pays: United States
ID NLM: 9419065
Informations de publication
Date de publication:
15 02 2022
15 02 2022
Historique:
revised:
24
10
2021
received:
05
08
2021
accepted:
31
10
2021
pubmed:
17
11
2021
medline:
29
3
2022
entrez:
16
11
2021
Statut:
ppublish
Résumé
During normal aging, the brain undergoes structural and functional changes. Many studies applied static functional connectivity (FC) analysis on resting state functional magnetic resonance imaging (rs-fMRI) data showing a link between aging and the increase of between-networks connectivity. However, it has been demonstrated that FC is not static but varies over time. By employing the dynamic data-driven approach of Hidden Markov Models, this study aims to investigate how aging is related to specific characteristics of dynamic brain states. Rs-fMRI data of 88 subjects, equally distributed in young and old were analyzed. The best model resulted to be with six states, which we characterized not only in terms of FC and mean BOLD activation, but also uncertainty of the estimates. We found two states were mostly occupied by young subjects, whereas three other states by old subjects. A graph-based analysis revealed a decrease in strength with the increase of age, and an overall more integrated topology of states occupied by old subjects. Indeed, while young subjects tend to cycle in a loop of states characterized by a high segregation of the networks, old subjects' loops feature high integration, with a crucial intermediary role played by the dorsal attention network. These results suggest that the employed mathematical approach captures the complex and rich brain's dynamics underpinning the aging process.
Identifiants
pubmed: 34783122
doi: 10.1002/hbm.25714
pmc: PMC8764474
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1129-1144Informations de copyright
© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
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