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Leveraging the Adolescent Brain Cognitive Development Study to improve behavioral prediction from neuroimaging in smaller replication samples.
Makowski, Carolina; Brown, Timothy T; Zhao, Weiqi; Hagler, Donald J; Parekh, Pravesh; Garavan, Hugh; Nichols, Thomas E; Jernigan, Terry L; Dale, Anders M.
Afiliación
  • Makowski C; Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, California, USA.
  • Brown TT; Department of Radiology, University of California San Diego, La Jolla, California, USA.
  • Zhao W; Department of Neurosciences, University of California San Diego, La Jolla, California, USA.
  • Hagler DJ; Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, California, USA.
  • Parekh P; Department of Cognitive Science, University of California San Diego, La Jolla, California USA.
  • Garavan H; Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, California, USA.
  • Nichols TE; Department of Radiology, University of California San Diego, La Jolla, California, USA.
  • Jernigan TL; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
  • Dale AM; Department of Psychiatry, University of Vermont, Burlington, Vermont, USA.
bioRxiv ; 2023 Oct 01.
Article en En | MEDLINE | ID: mdl-37398195
Magnetic resonance imaging (MRI) is a popular and useful non-invasive method to map patterns of brain structure and function to complex human traits. Recently published observations in multiple large scale studies cast doubt upon these prospects, particularly for prediction of cognitive traits from structural and resting state functional MRI, which seems to account for little behavioral variability. We leverage baseline data from thousands of children in the Adolescent Brain Cognitive DevelopmentSM (ABCD®) Study to inform the replication sample size required with both univariate and multivariate methods across different imaging modalities to detect reproducible brain-behavior associations. We demonstrate that by applying multivariate methods to high-dimensional brain imaging data, we can capture lower dimensional patterns of structural and functional brain architecture that correlate robustly with cognitive phenotypes and are reproducible with only 41 individuals in the replication sample for working memory-related functional MRI, and ~100 subjects for structural MRI. Even with 100 random re-samplings of 50 subjects in the discovery sample, prediction can be adequately powered with 98 subjects in the replication sample for multivariate prediction of cognition with working memory task functional MRI. These results point to an important role for neuroimaging in translational neurodevelopmental research and showcase how findings in large samples can inform reproducible brain-behavior associations in small sample sizes that are at the heart of many investigators' research programs and grants.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos