Hand classification of fMRI ICA noise components

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,...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser: Griffanti, L, Douaud, G, Bijsterbosh, J, Evangelisti, S, Alfaro-Almagro, F, Glasser, M, Duff, E, Fitzgibbon, S, Westphal, R, Carone, D, Beckmann, C, Smith, S
Format: Journal article
Sprache:English
Veröffentlicht: Elsevier 2016

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