EEG function network analysis of left and right hand motor imagery
2017
Network analysis of signals originating from different parts of brain during
motor imagery(MI) has gained lots of interest recently. In this paper, we used EEG to construct the brain network during MI, and analyzed the topological characteristics of the EEG function network. It is found that the node degree and
clustering coefficientof the right hand MI is higher than the left hand MI on the nodes of right sensorimotor cortex, and the characteristic path length of the network is shorter for right hand MI than left hand MI. As for the right hand MI task, most subjects showed higher node degree and
clustering coefficienton the right sensorimotor cortex than the left sensorimotor cortex. We conclude that EEG network based measures, which captures the brain
information integratingcharacteristics during MI, may serve as useful features for classification in MI-BCI application, especially for BCI inefficiency subject.
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