title: Hand classification of fMRI ICA noise components.
abstract: 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 the results of unsupervised ones or to manually clean the data. In this paper we describe the main spatial and temporal features of ICs and provide general guidelines on how to evaluate these. Examples of signal and noise components are provided from a wide range of datasets (3T data, including examples from the UK Biobank and the Human Connectome Project, and 7T data), together with practical guidelines for their identification. Finally, we discuss how the data quality, data type and preprocessing can influence the characteristics of the ICs and present examples of particularly challenging datasets.
authors.affiliation: Centre for the functional MRI of the Brain (FMRIB), University of Oxford, United Kingdom. Electronic address: ludovica.griffanti@ndcn.ox.ac.uk.
authors.forename: Ludovica
authors.initials: L
authors.lastname: Griffanti
authors.affiliation: Centre for the functional MRI of the Brain (FMRIB), University of Oxford, United Kingdom.
authors.forename: Gwenaëlle
authors.initials: G
authors.lastname: Douaud
authors.affiliation: Centre for the functional MRI of the Brain (FMRIB), University of Oxford, United Kingdom.
authors.forename: Janine
authors.initials: J
authors.lastname: Bijsterbosch
authors.affiliation: Centre for the functional MRI of the Brain (FMRIB), University of Oxford, United Kingdom; Functional MR Unit, Policlinico S. Orsola - Malpighi, Bologna, Italy - Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy.
authors.forename: Stefania
authors.initials: S
authors.lastname: Evangelisti
authors.affiliation: Centre for the functional MRI of the Brain (FMRIB), University of Oxford, United Kingdom.
authors.forename: Fidel
authors.initials: F
authors.lastname: Alfaro-Almagro
authors.affiliation: Washington University School of Medicine, Washington University, St. Louis, MO, USA.
authors.forename: Matthew F
authors.initials: MF
authors.lastname: Glasser
authors.affiliation: Centre for the functional MRI of the Brain (FMRIB), University of Oxford, United Kingdom.
authors.forename: Eugene P
authors.initials: EP
authors.lastname: Duff
authors.affiliation: Centre for the functional MRI of the Brain (FMRIB), University of Oxford, United Kingdom.
authors.forename: Sean
authors.initials: S
authors.lastname: Fitzgibbon
authors.affiliation: Department of Psychiatry, University of Oxford, United Kingdom.
authors.forename: Robert
authors.initials: R
authors.lastname: Westphal
authors.affiliation: Acute Stroke Programme, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom; Laboratory of Experimental Stroke Research, Department of Surgery and Translational Medicine, University of Milano Bicocca, Milan Center of Neuroscience, Monza, Italy.
authors.forename: Davide
authors.initials: D
authors.lastname: Carone
authors.affiliation: Centre for the functional MRI of the Brain (FMRIB), University of Oxford, United Kingdom; Department of Cognitve Neuroscience, Radboudumc and Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
authors.forename: Christian F
authors.initials: CF
authors.lastname: Beckmann
authors.affiliation: Centre for the functional MRI of the Brain (FMRIB), University of Oxford, United Kingdom.
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Smith
mesh_terms: D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging*; D002648:Child; D059907:Functional Neuroimaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*