Comput. Biol. Med. - EEG-based functional networks in schizophrenia.

Tópicos

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Resumo

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.

Resumo Limpo

schizophrenia often consid dysconnect syndrom abnorm interact largescal function brain network result cognit perceptu deficit articl appli graph theoret measur brain function network base rest eeg fourteen schizophren patient comparison fourteen match control subject network extract commonaveragereferenc eeg timeseri partial unparti crosscorrel method unparti correl detect function connect base direct andor indirect link partial correl allow one ignor indirect link quantifi network properti graph metric includ mallworld vulner modular assort synchroniz schizophren patient show methodspecif frequencyspecif chang especi pronounc modular assort synchroniz measur howev differ schizophrenia patient normal control term graph theori metric stronger unparti correl method

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