Leveraging the adolescent brain cognitive development study to improve behavioral prediction from neuroimaging in smaller replication samples

Author:

Makowski Carolina12ORCID,Brown Timothy T3,Zhao Weiqi14ORCID,Hagler Jr Donald J12,Parekh Pravesh56,Garavan Hugh7,Nichols Thomas E8910,Jernigan Terry L4,Dale Anders M123

Affiliation:

1. Center for Multimodal Imaging and Genetics, University of California San Diego , La Jolla, CA , United States

2. Department of Radiology, University of California San Diego , La Jolla, CA , United States

3. Department of Neurosciences, University of California San Diego , La Jolla, CA, , United States

4. Department of Cognitive Science, University of California San Diego , La Jolla, CA , United States

5. NORMENT , Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, , Oslo , Norway

6. University of Oslo , Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, , Oslo , Norway

7. Department of Psychiatry, University of Vermont , Burlington, VT , United States

8. Nuffield Department of Clinical Neurosciences, University of Oxford , Oxford , United Kingdom

9. Wellcome Centre for Integrative Neuroimaging , FMRIB, Nuffield Department of Clinical Neurosciences, , Oxford , United Kingdom

10. University of Oxford , FMRIB, Nuffield Department of Clinical Neurosciences, , Oxford , United Kingdom

Abstract

Abstract Neuroimaging is a popular method to map brain structural and functional patterns to complex human traits. Recently published observations cast doubt upon these prospects, particularly for prediction of cognitive traits from structural and resting state functional magnetic resonance imaging (MRI). We leverage baseline data from thousands of children in the Adolescent Brain Cognitive DevelopmentSM Study to inform the replication sample size required with 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 and resting state MRI. Even with 100 random re-samplings of 100 subjects in discovery, prediction can be adequately powered with 66 subjects in replication 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 research programs and grants.

Funder

Adolescent Brain Cognitive DevelopmentSM

NIMH Data Archive

National Institutes of Health

Publisher

Oxford University Press (OUP)

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