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      Reproducible brain-wide association studies require thousands of individuals

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      1 , , 2 , 3 , ,   4 , 5 , 6 , 6 , 1 , 1 , 4 , 1 , 6 , 7 , 8 , 1 , 9 , 10 , 9 , 10 , 11 , 9 , 11 , 9 , 11 , 11 , 11 , 11 , 9 , 11 , 11 , 11 , 9 , 12 , 9 , 12 , 7 , 13 , 14 , 15 , 16 , 13 , 14 , 15 , 16 , 6 , 6 , 6 , 6 , 17 , 6 , 6 , 1 , 18 , 6 , 17 , 19 , 20 , 21 , 22 , 23 , 24 , 13 , 14 , 15 , 16 , 25 , 26 , 1 , 21 , 3 , 4 , 9 , 10 , 27 , , 6 , 17 , 19 , 28 , 29 ,
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      Nature Publishing Group UK
      Cognitive neuroscience, Psychology

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          Abstract

          Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions 13 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping 4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain–behavioural phenotype associations 5, 6 . Here we used three of the largest neuroimaging datasets currently available—with a total sample size of around 50,000 individuals—to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain–phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.

          Abstract

          Combined data from three large studies, with a total sample size of around 50,000 individuals, indicate that many previous studies linking the brain to complex phenotypes have been statistically underpowered, producing inflated and irreproducible effects.

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          Most cited references67

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          UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

          Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
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            FSL.

            FSL (the FMRIB Software Library) is a comprehensive library of analysis tools for functional, structural and diffusion MRI brain imaging data, written mainly by members of the Analysis Group, FMRIB, Oxford. For this NeuroImage special issue on "20 years of fMRI" we have been asked to write about the history, developments and current status of FSL. We also include some descriptions of parts of FSL that are not well covered in the existing literature. We hope that some of this content might be of interest to users of FSL, and also maybe to new research groups considering creating, releasing and supporting new software packages for brain image analysis. Copyright © 2011 Elsevier Inc. All rights reserved.
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              Cortical surface-based analysis. I. Segmentation and surface reconstruction.

              Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging. Copyright 1999 Academic Press.
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                Author and article information

                Contributors
                smarek@wustl.edu
                btervo-clemmens@mgh.harvard.edu
                faird@umn.edu
                ndosenbach@wustl.edu
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                16 March 2022
                16 March 2022
                2022
                : 603
                : 7902
                : 654-660
                Affiliations
                [1 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Department of Psychiatry, , Washington University School of Medicine, ; St Louis, MO USA
                [2 ]GRID grid.32224.35, ISNI 0000 0004 0386 9924, Department of Psychiatry, , Massachusetts General Hospital, Harvard Medical School, ; Boston, MA USA
                [3 ]GRID grid.21925.3d, ISNI 0000 0004 1936 9000, Department of Psychology, , University of Pittsburgh, ; Pittsburgh, PA USA
                [4 ]GRID grid.21925.3d, ISNI 0000 0004 1936 9000, Department of Psychiatry, , University of Pittsburgh, ; Pittsburgh, PA USA
                [5 ]GRID grid.21925.3d, ISNI 0000 0004 1936 9000, Department of Bioengineering, , University of Pittsburgh, ; Pittsburgh, PA USA
                [6 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Department of Neurology, , Washington University School of Medicine, ; St Louis, MO USA
                [7 ]GRID grid.17635.36, ISNI 0000000419368657, University of Minnesota Informatics Institute, University of Minnesota, ; Minneapolis, MN USA
                [8 ]GRID grid.17635.36, ISNI 0000000419368657, Department of Psychology, , University of Minnesota, ; Minneapolis, MN USA
                [9 ]GRID grid.17635.36, ISNI 0000000419368657, Masonic Institute for the Developing Brain, , University of Minnesota Medical School, ; Minneapolis, MN USA
                [10 ]GRID grid.17635.36, ISNI 0000000419368657, Department of Pediatrics, , University of Minnesota Medical School, ; Minneapolis, MN USA
                [11 ]GRID grid.5288.7, ISNI 0000 0000 9758 5690, Department of Psychiatry, , Oregon Health and Science University, ; Portland, OR USA
                [12 ]GRID grid.17635.36, ISNI 0000000419368657, Minnesota Supercomputing Institute, , University of Minnesota, ; Minneapolis, MN USA
                [13 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, Department of Electrical and Computer Engineering, , National University of Singapore, ; Singapore, Singapore
                [14 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, Centre for Sleep and Cognition, , National University of Singapore, ; Singapore, Singapore
                [15 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, Centre for Translational MR Research, , National University of Singapore, ; Singapore, Singapore
                [16 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, N.1 Institute for Health, Institute for Digital Medicine, , National University of Singapore, ; Singapore, Singapore
                [17 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Department of Biomedical Engineering, , Washington University in St Louis, ; St Louis, MO USA
                [18 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Cognitive Science, , University of California San Diego, ; La Jolla, CA USA
                [19 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Department of Radiology, , Washington University School of Medicine, ; St Louis, MO USA
                [20 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Department of Neurological Surgery, , Washington University School of Medicine, ; St Louis, MO USA
                [21 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Department of Psychological and Brain Sciences, , Washington University in St Louis, ; St Louis, MO USA
                [22 ]GRID grid.59062.38, ISNI 0000 0004 1936 7689, Department of Psychiatry, , University of Vermont, ; Burlington, VT USA
                [23 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Division of Biostatistics, , University of California San Diego, ; La Jolla, CA USA
                [24 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, , University of Oxford, ; Oxford, UK
                [25 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, Integrative Sciences and Engineering Programme, , National University of Singapore, ; Singapore, Singapore
                [26 ]GRID grid.32224.35, ISNI 0000 0004 0386 9924, Martinos Center for Biomedical Imaging, , Massachusetts General Hospital, ; Charlestown, MA USA
                [27 ]GRID grid.17635.36, ISNI 0000000419368657, Institute of Child Development, , University of Minnesota Medical School, ; Minneapolis, MN USA
                [28 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Program in Occupational Therapy, , Washington University School of Medicine, ; St Louis, MO USA
                [29 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Department of Pediatrics, , Washington University School of Medicine, ; St Louis, MO USA
                Author information
                http://orcid.org/0000-0003-0032-9052
                http://orcid.org/0000-0002-9557-1126
                http://orcid.org/0000-0002-8092-3942
                http://orcid.org/0000-0001-5512-0083
                http://orcid.org/0000-0003-3957-2949
                http://orcid.org/0000-0002-7665-2713
                http://orcid.org/0000-0001-7310-2022
                http://orcid.org/0000-0001-6752-5707
                http://orcid.org/0000-0003-1511-1515
                http://orcid.org/0000-0001-5786-4705
                http://orcid.org/0000-0002-0739-7771
                http://orcid.org/0000-0002-4516-5103
                http://orcid.org/0000-0003-1693-8506
                http://orcid.org/0000-0001-8602-393X
                http://orcid.org/0000-0002-6876-7078
                Article
                4492
                10.1038/s41586-022-04492-9
                8991999
                35296861
                436cbfb4-4d04-4612-b549-ec303a7dfc17
                © The Author(s), under exclusive licence to Springer Nature Limited 2022, corrected publication 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 19 May 2021
                : 31 January 2022
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                © The Author(s), under exclusive licence to Springer Nature Limited 2022

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                cognitive neuroscience,psychology
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                cognitive neuroscience, psychology

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