High-amplitude network co-fluctuations linked to variation in hormone concentrations over the menstrual cycle.
Edge-centric
Functional connectivity
Time-varying networks
Journal
Network neuroscience (Cambridge, Mass.)
ISSN: 2472-1751
Titre abrégé: Netw Neurosci
Pays: United States
ID NLM: 101719149
Informations de publication
Date de publication:
2023
2023
Historique:
received:
08
09
2021
accepted:
20
12
2022
medline:
2
10
2023
pubmed:
2
10
2023
entrez:
2
10
2023
Statut:
epublish
Résumé
Many studies have shown that the human endocrine system modulates brain function, reporting associations between fluctuations in hormone concentrations and brain connectivity. However, how hormonal fluctuations impact fast changes in brain network organization over short timescales remains unknown. Here, we leverage a recently proposed framework for modeling co-fluctuations between the activity of pairs of brain regions at a framewise timescale. In previous studies we showed that time points corresponding to high-amplitude co-fluctuations disproportionately contributed to the time-averaged functional connectivity pattern and that these co-fluctuation patterns could be clustered into a low-dimensional set of recurring "states." Here, we assessed the relationship between these network states and quotidian variation in hormone concentrations. Specifically, we were interested in whether the frequency with which network states occurred was related to hormone concentration. We addressed this question using a dense-sampling dataset (
Identifiants
pubmed: 37781152
doi: 10.1162/netn_a_00307
pii: netn_a_00307
pmc: PMC10473261
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1181-1205Informations de copyright
© 2023 Massachusetts Institute of Technology.
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