Head motion during the acquisition of fMRI data can significantly contaminate the neural signal and induce spurious, distance-dependent changes in signal correlations. Framewise displacement (FD) has often been used as a cut-off threshold for removing bad fMRI datasets related with high motion. Here we investigated the influence of head motion on the output of ICA-based denoising analysis. The results showed a strong correlation between the number of total ICA components with head mean motion and FD, which indicated that the number of ICA components can be an index for detecting high motion-related fMRI datasets.
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