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Wu et al. have made an important contribution to the methodology for data-driven analysis of MRI data. However, we wish to challenge the authors on new potential applications of their approach beyond diffusion tensor imaging data, and to think carefully about the impact of random initialization implicit in their method. We illustrate the variability found from re-analyzing the supplied demonstration data multiple times, finding that the discovered independent components have a wide range of reliability, from nearly perfect overlap to no overlap at all.

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DTI, fMRI, independent component analysis, multimodality neuroimaging