Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity

Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity

Denoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., ‘motion’ parameters). However, it is increasingly recognized that r...

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Bibliographic Details
Main Authors: Caterina Gratton, Ally Dworetsky, Rebecca S. Coalson, Babatunde Adeyemo, Timothy O. Laumann, Gagan S. Wig, Tania S. Kong, Gabriele Gratton, Monica Fabiani, Deanna M. Barch, Daniel Tranel, Oscar Miranda-Dominguez, Damien A. Fair, Nico U.F. Dosenbach, Abraham Z. Snyder, Joel S. Perlmutter, Steven E. Petersen, Meghan C. Campbell
Format: Article
Language:English
Published: Elsevier 2020-08-01
Series:NeuroImage
Subjects:
fMRI
Motion
Artifacts
Aging
Functional connectivity
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811920303529

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http://www.sciencedirect.com/science/article/pii/S1053811920303529

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