Hand classification of fMRI ICA noise components

We present a practical “how-to” guide to help determine whether single-subject fMRI independent components (ICs) characterise structured noise or not. Manual identification of signal and noise after ICA decomposition is required for efficient data denoising: to train supervised algorithms, to check...

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Bibliographic Details
Published in:	NeuroImage (Orlando, Fla.) Vol. 154; pp. 188 - 205
Main Authors:	Griffanti, Ludovica, Douaud, Gwenaëlle, Bijsterbosch, Janine, Evangelisti, Stefania, Alfaro-Almagro, Fidel, Glasser, Matthew F., Duff, Eugene P., Fitzgibbon, Sean, Westphal, Robert, Carone, Davide, Beckmann, Christian F., Smith, Stephen M.
Format:	Journal Article
Language:	English
Published:	United States Elsevier Inc 01.07.2017 Elsevier Limited Academic Press
Subjects:	Adult Algorithms Brain - diagnostic imaging Child Classification Data processing Decomposition Functional magnetic resonance imaging Functional Neuroimaging - methods Humans Identification Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging - methods Methods NMR Noise Nuclear magnetic resonance Temporal variations Time series
ISSN:	1053-8119, 1095-9572, 1095-9572
Online Access:	Get full text
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