Harnessing mega-analysis in the era of “big data” neuroimaging
Author:
Funder
U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute
U.S. Department of Health & Human Services | NIH | National Institute of Mental Health
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41386-024-01964-6.pdf
Reference6 articles.
1. Norman LJ, Sudre G, Price J, Shastri GG, Shaw P. Evidence from “big data” for the default-mode hypothesis of ADHD: a mega-analysis of multiple large samples. Neuropsychopharmacology. 2023;48:281–89.
2. Norman LJ, Sudre G, Price J, Shaw P. Subcortico-cortical dysconnectivity in ADHD: a voxel-wise mega-analysis across multiple cohorts. Am J Psychiatry. 2024;181:553–62.
3. Hoogman M, Van Rooij D, Klein M, Boedhoe P, Ilioska I, Li T, et al. Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: the ENIGMA adventure. Hum Brain Mapp. 2020;43:37–55.
4. Sudre G, Norman L, Bouyssi-Kobar M, Price J, Shastri GG, Shaw P. A mega-analytic study of white matter microstructural differences across 5 cohorts of youths with attention-deficit/hyperactivity disorder. Biol Psychiatry. 2023;94:18–28.
5. Mooney MA, Hermosillo RJ, Feczko E, Miranda-Dominguez O, Moore LA, Perrone A, et al. Cumulative effects of resting-state connectivity across all brain networks significantly correlate with ADHD symptoms. J Neurosci. 2024;44:e1202232023.
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