Classification of temporal ICA components for separating global noise from fMRI data: Reply to Power

Matthew F. Glasser, Timothy S. Coalson, Janine D. Bijsterbosch, Samuel J. Harrison, Michael P. Harms, Alan Anticevic, David C. Van Essen, Stephen M. Smith

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)435-438
Number of pages4
JournalNeuroImage
Volume197
DOIs
StatePublished - Aug 15 2019

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