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

Authors :
Olivia Gosseries
Ahmad Mheich
Mahmoud Hassan
Helena Cassol
Rajanikant Panda
Sepehr Mortaheb
Fabrice Wendling
Camille Chatelle
Steven Laureys
Pascal Benquet
Jitka Annen
Hassan Amoud
Aurore Thibaut
Jennifer Rizkallah
Julien Modolo
Jonchère, Laurent
Laboratoire Traitement du Signal et de l'Image (LTSI)
Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Centre Hospitalier Universitaire de Liège (CHU-Liège)
686764, Future Emerging Technologies
University and University Hospital of Liège
Belgian National Funds for Scientific Research
ARC - 06/11 - 340, French Speaking Community Concerted Research Action
Université de Rennes 1 (UR1)
Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Source :
Neuroimage-Clinical, Neuroimage-Clinical, 2019, 23, pp.101841. ⟨10.1016/j.nicl.2019.101841⟩, Neuroimage-Clinical, Elsevier, 2019, 23, pp.101841. ⟨10.1016/j.nicl.2019.101841⟩, NeuroImage: Clinical, NeuroImage: Clinical, Vol 23, Iss, Pp-(2019)
Publication Year :
2019
Publisher :
HAL CCSD, 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
Database :
OpenAIRE
Journal :
Neuroimage-Clinical, Neuroimage-Clinical, 2019, 23, pp.101841. ⟨10.1016/j.nicl.2019.101841⟩, Neuroimage-Clinical, Elsevier, 2019, 23, pp.101841. ⟨10.1016/j.nicl.2019.101841⟩, NeuroImage: Clinical, NeuroImage: Clinical, Vol 23, Iss, Pp-(2019)
Accession number :
edsair.doi.dedup.....c41e11b1c2bb7a40544ee2a1dc38df6a