Document Type : Full Research Paper

Authors

1 Ms Student, Bioelectric Department, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran

2 Professor, Bioelectric Department, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran

3 Assistant Professor, Bioelectric Department, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran

Abstract

The aim of this paper is to study brain effective connectivity based on directed transform function (DTF) using granger causality method. This connectivity was calculated for recorded data in different states of attention and consciousness, forming four different classes: attention-consciousness, attention-unconsciousness, inattention-consciousness, and inattention-unconsciousness. Some common indices were extracted and calculated from the connectivity matrices. Indices of these four classes were compared to see whether there is a significant difference among them or not. The Multivariate Autoregressive (MVAR) model was used to obtain the linear causal relations between channels. Furthermore, signals were divided into four frequency bands for more accurate investigation, and the existence of significant difference was investigated with two-way repeated measures test. Results indicated that  and  among twelve indices could show a significant difference (p<0.05)  in five states out of six possible states. The only state that no feature was able to show a meaningful difference was inattention-consciousness, and inattention-unconsciousness.

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