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Science Foundation in China

Mean mutual information ratio: a new method for ranking components of ICA
Zuo Xinian, Zhu Chaozhe and Zang Yufeng
1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China; 2. State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
Abstract:  This paper aims to develop a more robust measure of independency called mean mutual information ratio and propose a new way for ranking components with this measure. In order to evaluate the advantage of mean mutual information ratio, independent component analysis has been performed on task-related and resting-state functional magnetic resonance imaging data. And then, mean mutual information ratio was compared to kurtosis in ranking components. The result demonstrated that mean mutual information ratio gives more accurate and robust measure of independency.
Keywords:  independent component analysis, mutual information, default mode, fMRI
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