EEG microstate temporal Dynamics Predict depressive symptoms in College Students.
Depressive symptoms
EEG microstates
Temporal dynamics
Transition probabilities
Journal
Brain topography
ISSN: 1573-6792
Titre abrégé: Brain Topogr
Pays: United States
ID NLM: 8903034
Informations de publication
Date de publication:
07 2022
07 2022
Historique:
received:
05
12
2021
accepted:
19
05
2022
pubmed:
6
7
2022
medline:
2
8
2022
entrez:
5
7
2022
Statut:
ppublish
Résumé
Previous studies on resting-state electroencephalographic responses in patients with depressive disorders have identified electroencephalogram (EEG) parameters as potential biomarkers for the early detection and diagnosis of depressive disorders. However, these studies did not investigate the relationship between resting-state EEG microstates and the early detection of depressive symptoms in preclinical individuals. To explore the possible association between resting-state EEG microstate temporal dynamics and depressive symptoms among college students, EEG microstate analysis was performed on eyes-closed resting-state EEG data for approximately 5 min from 34 undergraduates with high intensity of depressive symptoms and 34 age- and sex-matched controls with low intensity of depressive symptoms. Five microstate classes (A-E) were identified to best explain the datasets of both groups. Compared to controls, the mean duration, occurrence, and coverage of microstate class B increased significantly, whereas the occurrence and coverage of microstate classes D and E decreased significantly in individuals with high intensity of depressive symptoms. Additionally, the presence of microstate class B was positively correlated with participants' Beck Depression Inventory-II (BDI-II) scores, and the presence of microstate classes D and E were negatively correlated with their BDI-II scores. Further, individuals with high intensity of depressive symptoms had higher transition probabilities of A→B, B→A, B→C, B→D, and C→B, with lower transition probabilities of A→D, A→E, D→A, D→E, E→A, E→C, and E→D than controls. These results highlight resting-state EEG microstate temporal dynamics as potential biomarkers for the early detection and timely treatment of depression in college students.
Identifiants
pubmed: 35790705
doi: 10.1007/s10548-022-00905-0
pii: 10.1007/s10548-022-00905-0
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
481-494Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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