Evaluating functional connectivity in alcoholics based on maximal weight matching

Zhu, Guohun and Li, Yan and Wen, Peng (2011) Evaluating functional connectivity in alcoholics based on maximal weight matching. Journal of Advanced Computational Intelligence and Intelligent Informatics, 15 (9). pp. 1221-1227. ISSN 1343-0130

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Abstract

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

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Item Type:	Article (Commonwealth Reporting Category C)
Refereed:	Yes
Item Status:	Live Archive
Additional Information:	Deposited in accordance with the copyright policy of the publisher. (Fuji Technology Press) http://www.fujipress.jp/JRM/pdf/rb_copyright.pdf
Faculty/School / Institute/Centre:	Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013)
Faculty/School / Institute/Centre:	Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013)
Date Deposited:	02 Feb 2012 07:07
Last Modified:	26 Aug 2014 21:28
Uncontrolled Keywords:	EEG; greedy maximal weight matching; synchronization; repeated and unrepeated stimuli
Fields of Research (2008):	10 Technology > 1004 Medical Biotechnology > 100402 Medical Biotechnology Diagnostics (incl. Biosensors) 01 Mathematical Sciences > 0102 Applied Mathematics > 010202 Biological Mathematics 17 Psychology and Cognitive Sciences > 1702 Cognitive Sciences > 170205 Neurocognitive Patterns and Neural Networks
Socio-Economic Objectives (2008):	E Expanding Knowledge > 97 Expanding Knowledge > 970102 Expanding Knowledge in the Physical Sciences
URI:	http://eprints.usq.edu.au/id/eprint/20433

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