Confound modelling in UK Biobank brain imaging.

Big data imaging Confounds Data modelling Epidemiological studies Image analysis Machine learning Multi-modal data integration Statistica l modelling

Journal

NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515

Informations de publication

Date de publication:
01 01 2021
Historique:
received: 11 03 2020
revised: 08 05 2020
accepted: 25 05 2020
pubmed: 6 6 2020
medline: 30 3 2021
entrez: 6 6 2020
Statut: ppublish

Résumé

Dealing with confounds is an essential step in large cohort studies to address problems such as unexplained variance and spurious correlations. UK Biobank is a powerful resource for studying associations between imaging and non-imaging measures such as lifestyle factors and health outcomes, in part because of the large subject numbers. However, the resulting high statistical power also raises the sensitivity to confound effects, which therefore have to be carefully considered. In this work we describe a set of possible confounds (including non-linear effects and interactions that researchers may wish to consider for their studies using such data). We include descriptions of how we can estimate the confounds, and study the extent to which each of these confounds affects the data, and the spurious correlations that may arise if they are not controlled. Finally, we discuss several issues that future studies should consider when dealing with confounds.

Identifiants

pubmed: 32502668
pii: S1053-8119(20)30488-2
doi: 10.1016/j.neuroimage.2020.117002
pmc: PMC7610719
mid: EMS123322
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

117002

Subventions

Organisme : Wellcome Trust
ID : 098369/Z/12/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 098369
Pays : United Kingdom
Organisme : Medical Research Council
Pays : United Kingdom
Organisme : Department of Health
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 203139/Z/16/Z
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 203139
Pays : United Kingdom

Informations de copyright

Copyright © 2020. Published by Elsevier Inc.

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Auteurs

Fidel Alfaro-Almagro (F)

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK. Electronic address: fidel.alfaroalmagro@ndcn.ox.ac.uk.

Paul McCarthy (P)

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.

Soroosh Afyouni (S)

Big Data Institute, University of Oxford, UK.

Jesper L R Andersson (JLR)

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.

Matteo Bastiani (M)

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, UK; NIHR Biomedical Research Centre, University of Nottingham, UK.

Karla L Miller (KL)

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.

Thomas E Nichols (TE)

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Big Data Institute, University of Oxford, UK.

Stephen M Smith (SM)

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.

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