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Decreased integration of EEG source-space networks in disorders of consciousness

Authors :
Jennifer Rizkallah
Jitka Annen
Julien Modolo
Olivia Gosseries
Pascal Benquet
Sepehr Mortaheb
Hassan Amoud
Helena Cassol
Ahmad Mheich
Aurore Thibaut
Camille Chatelle
Mahmoud Hassan
Rajanikant Panda
Fabrice Wendling
Steven Laureys
Source :
NeuroImage: Clinical, Vol 23, Iss , Pp - (2019)
Publication Year :
2019
Publisher :
Elsevier, 2019.

Abstract

Increasing evidence links disorders of consciousness (DOC) with disruptions in functional connectivity between distant brain areas. However, to which extent the balance of brain network segregation and integration is modified in DOC patients remains unclear. Using high-density electroencephalography (EEG), the objective of our study was to characterize the local and global topological changes of DOC patients' functional brain networks.Resting state high-density-EEG data were collected and analyzed from 82 participants: 61 DOC patients recovering from coma with various levels of consciousness (EMCS (n = 6), MCS+ (n = 29), MCS- (n = 17) and UWS (n = 9)), and 21 healthy subjects (i.e., controls). Functional brain networks in five different EEG frequency bands and the broadband signal were estimated using an EEG connectivity approach at the source level. Graph theory-based analyses were used to evaluate their relationship with decreasing levels of consciousness as well as group differences between healthy volunteers and DOC patient groups.Results showed that networks in DOC patients are characterized by impaired global information processing (network integration) and increased local information processing (network segregation) as compared to controls. The large-scale functional brain networks had integration decreasing with lower level of consciousness. Keywords: Disorders of consciousness, High-density electroencephalography, Functional brain networks, Unresponsive wakefulness syndrome, Minimally conscious state

Details

Language :
English
ISSN :
22131582
Volume :
23
Issue :
-
Database :
Directory of Open Access Journals
Journal :
NeuroImage: Clinical
Publication Type :
Academic Journal
Accession number :
edsdoj.9c9910702e2f4532881a9cda2ff97830
Document Type :
article
Full Text :
https://doi.org/10.1016/j.nicl.2019.101841