EEG-based functional networks in schizophrenia.

Détails

ID Serval
serval:BIB_D9071F28186D
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
EEG-based functional networks in schizophrenia.
Périodique
Computers in Biology and Medicine
Auteur⸱e⸱s
Jalili M., Knyazeva M.G.
ISSN
1879-0534 (Electronic)
ISSN-L
0010-4825
Statut éditorial
Publié
Date de publication
2011
Volume
41
Numéro
12
Pages
1178-1186
Langue
anglais
Notes
Publication types: Journal ArticlePublication Status: ppublish
Résumé
Schizophrenia is often considered as a dysconnection syndrome in which, abnormal interactions between large-scale functional brain networks result in cognitive and perceptual deficits. In this article we apply the graph theoretic measures to brain functional networks based on the resting EEGs of fourteen schizophrenic patients in comparison with those of fourteen matched control subjects. The networks were extracted from common-average-referenced EEG time-series through partial and unpartial cross-correlation methods. Unpartial correlation detects functional connectivity based on direct and/or indirect links, while partial correlation allows one to ignore indirect links. We quantified the network properties with the graph metrics, including mall-worldness, vulnerability, modularity, assortativity, and synchronizability. The schizophrenic patients showed method-specific and frequency-specific changes especially pronounced for modularity, assortativity, and synchronizability measures. However, the differences between schizophrenia patients and normal controls in terms of graph theory metrics were stronger for the unpartial correlation method.
Pubmed
Web of science
Création de la notice
24/02/2012 11:45
Dernière modification de la notice
20/08/2019 16:58
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