Evaluating Functional Connectivity in Alcoholics Based on Maximal Weight Matching

EEG-based applications have faced the challenge of multi-modal integrated analysis problems. In this paper, a greedy maximal weight matching approach is used to measure the functional connectivity in alcoholics datasets with EEG and EOG signals. The major discovery is that the processing of the repe...

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Bibliographic Details
Published inJournal of advanced computational intelligence and intelligent informatics Vol. 15; no. 9; pp. 1221 - 1227
Main Authors Zhu, Guohun, Li, Yan, Wen, Peng (Paul)
Format Journal Article
LanguageEnglish
Published 20.11.2011
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Summary:EEG-based applications have faced the challenge of multi-modal integrated analysis problems. In this paper, a greedy maximal weight matching approach is used to measure the functional connectivity in alcoholics datasets with EEG and EOG signals. The major discovery is that the processing of the repeated and unrepeated stimuli in the γ band in control drinkers is significantly more different than that in alcoholic subjects. However, the EOGs are always stable in the case of visual tasks, except for a weakly wave when subjects make an error response to the stimuli.
ISSN:1343-0130
1883-8014
DOI:10.20965/jaciii.2011.p1221