Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
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The lack of consistent ordering of components resulted from independent component analysis poses a significant obstacle to the pervasive application of this method on fMRI data analysis. Based on the temporal correlation of physiological noise components of fMRI data and that of cerebrospinal fluid data, the ordering of independent spatial components is ranked using canonical correlation analysis. The proposed method can robustly identify the task-related spatial component without any prior information about the functional activation paradigm. The experimental results of analyzing the real fMRI data show the reliability of the presented method.