Hand classification of fMRI ICA noise components

• 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

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...