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Leveraging the Adolescent Brain Cognitive Development Study to improve behavioral prediction from neuroimaging in smaller replication samples
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312746/ https://www.ncbi.nlm.nih.gov/pubmed/37398195 http://dx.doi.org/10.1101/2023.06.16.545340 |
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author | Makowski, Carolina Brown, Timothy T. Zhao, Weiqi Hagler, Donald J. Parekh, Pravesh Garavan, Hugh Nichols, Thomas E. Jernigan, Terry L. Dale, Anders M. |
author_facet | Makowski, Carolina Brown, Timothy T. Zhao, Weiqi Hagler, Donald J. Parekh, Pravesh Garavan, Hugh Nichols, Thomas E. Jernigan, Terry L. Dale, Anders M. |
author_sort | Makowski, Carolina |
collection | PubMed |
description | 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 Development(SM) (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. |
format | Online Article Text |
id | pubmed-10312746 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-103127462023-07-01 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. bioRxiv Article 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 Development(SM) (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. Cold Spring Harbor Laboratory 2023-10-01 /pmc/articles/PMC10312746/ /pubmed/37398195 http://dx.doi.org/10.1101/2023.06.16.545340 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Makowski, Carolina Brown, Timothy T. Zhao, Weiqi Hagler, Donald J. Parekh, Pravesh Garavan, Hugh Nichols, Thomas E. Jernigan, Terry L. Dale, Anders M. Leveraging the Adolescent Brain Cognitive Development Study to improve behavioral prediction from neuroimaging in smaller replication samples |
title | Leveraging the Adolescent Brain Cognitive Development Study to improve behavioral prediction from neuroimaging in smaller replication samples |
title_full | Leveraging the Adolescent Brain Cognitive Development Study to improve behavioral prediction from neuroimaging in smaller replication samples |
title_fullStr | Leveraging the Adolescent Brain Cognitive Development Study to improve behavioral prediction from neuroimaging in smaller replication samples |
title_full_unstemmed | Leveraging the Adolescent Brain Cognitive Development Study to improve behavioral prediction from neuroimaging in smaller replication samples |
title_short | Leveraging the Adolescent Brain Cognitive Development Study to improve behavioral prediction from neuroimaging in smaller replication samples |
title_sort | leveraging the adolescent brain cognitive development study to improve behavioral prediction from neuroimaging in smaller replication samples |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312746/ https://www.ncbi.nlm.nih.gov/pubmed/37398195 http://dx.doi.org/10.1101/2023.06.16.545340 |
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