Year: 2026
Type: article
Abstract: Recent work suggests that thousands of individuals are required in multivariate brain-behaviour analyses to obtain consistently replicable results. Some believe, however, that smaller sample sizes may be sufficient if specific subpopulations are targeted. We investigated how sample size and cohort composition influence the replicability of Canonical Correlation Analysis (CCA) results using the UK Biobank (N=40,514). We applied CCA to diffusion-weighted magnetic resonance imaging (dMRI) phenotypes and cognitive assessment test scores. We defined four participant cohorts based on clinical profile and found that, across all cohorts, sample sizes of around 500 were needed to obtain replicable canonical correlations and variable loadings. The most targeted cohort required much fewer samples to achieve similar or greater correlations than the other cohorts. Variable loadings were consistent between sample sizes of ~500 to thousands, suggesting that sample sizes in the order of hundreds may be sufficient for obtaining reliable CCA results.
Source: Communications Biology
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,190
Funders: Michael J. Fox Foundation for Parkinson's Research, Amazon Web Services, McGill University, Fondation Brain Canada, Wellcome Trust, Canadian Bee Research Fund, Ministère de l'Économie, de l’Innovation et des Exportations du Québec, Government of Canada, Canada First Research Excellence Fund, Alliance de recherche numérique du Canada, National Institutes of Health, Health Canada, Canadian Institutes of Health Research, Fonds de Recherche du Québec - Santé, Fonds de recherche du Québec – Nature et technologies, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering
Awards: G190208471, G1956579886, G2090471710, G3443250983, G3482984170, The Neuroimaging Data Model: FAIR descriptors of Brain Initiative Imaging Experiments, G4053145978, Development and validation of multi modal Parkinson's disease subtyping and progression biomarkers in multiple cohorts, Developing an international governance framework to advance global brain and mental health data equity and innovation, G7235187412, Bourses de maîtrise en recherche — Apprentissage et mémoire, Imagerie, G7934604842, G828718400, G83096887, Bourses de doctorat en recherche — Maladie de Parkinson, G9000007635, G9000014090, G9000022440, G9000172776, G9000222926, BRAIN CONNECTS: The Axonal Projectome EXchange (APEX)
OpenAlex ID: W7165868080
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