Journal
NEUROIMAGE
Volume 197, Issue -, Pages 435-438Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2019.04.046
Keywords
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Funding
- Human Connectome Project, WU-Minn-Ox Consortium - 16 NIH Institutes and Centers [1U54MH091657]
- McDonnell Center for Systems Neuroscience at Washington University
- NIH [F30 MH097312, RO1 MH-60974]
- Wellcome Trust strategic award [098369/Z/12/Z]
- Strategic Focus Area Personalized Health and Related Technologies (PHRT) of the ETH Domain [2017-403]
- Wellcome Trust [098369/Z/12/Z] Funding Source: Wellcome Trust
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We respond to a critique of our temporal Independent Components Analysis (ICA) method for separating global noise from global signal in fMRI data that focuses on the signal versus noise classification of several components. While we agree with several of Power's comments, we provide evidence and analysis to rebut his major criticisms and to reassure readers that temporal ICA remains a powerful and promising denoising approach.
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