Resting-state connectivity and network parameter analysis in alcohol-dependent males. A simultaneous EEG-MEG study.
EEG
MEG
alcohol dependence
functional connectivity
network parameters
phase-lag synchronization
Journal
Journal of neuroscience research
ISSN: 1097-4547
Titre abrégé: J Neurosci Res
Pays: United States
ID NLM: 7600111
Informations de publication
Date de publication:
10 2020
10 2020
Historique:
received:
11
01
2020
revised:
15
05
2020
accepted:
25
05
2020
pubmed:
26
6
2020
medline:
18
9
2021
entrez:
26
6
2020
Statut:
ppublish
Résumé
There is supporting evidence of alcohol negative effects on the brain: neuroimaging and psychophysiological studies finding anatomical and functional connectivity (FC) changes associated with the dependence process. Thus, the aim of this work was to evaluate brain FC and network characteristics of alcohol-dependent individuals in resting state. For this study, we included males diagnosed with alcohol dependence (N = 25) and a group of healthy individuals (N = 23). Simultaneous EEG-MEG (electroencephalographic and magnetoencephalographic) activity was recorded in 5 min of eyes-closed resting state. EEG-MEG activity was preprocessed and FC was computed through the leakage-corrected version of phase locking value (ciPLV). Additionally, local (degree, efficiency, clustering) and global (efficiency, characteristic path length) network parameters were computed. Connectivity analysis showed an increase in phase-lagged synchronization, mainly between frontal and frontotemporal regions, in high beta band, and a decrease in interhemispheric gamma, for alcohol-dependent individuals. Network analysis revealed intergroup differences at the local level for high beta, indicating higher degree, clustering, and efficiency, mostly at frontal nodes, together with a decrease in these measures at more posterior sites for patients' group. The hyper-synchronization in beta, next to the hypo-synchronization in gamma, could indicate an alteration in communication between hemispheres, but also a possible functional compensation mechanism in neural circuits. This could be also supported by network characteristic data, where local alterations in communication are observed.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1857-1876Informations de copyright
© 2020 Wiley Periodicals, Inc.
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