Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis

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Zhang-James, Y. orcid id iconORCID: https://orcid.org/0000-0002-2104-0963, Helminen, E. C., Liu, J., The ENIGMA-ADHD Working Group orcid id iconORCID: https://orcid.org/0000-0002-4267-3436, Franke, B. orcid id iconORCID: https://orcid.org/0000-0003-4375-6572, Hoogman, M. and Faraone, S. V. orcid id iconORCID: https://orcid.org/0000-0002-9217-3982 (2021) Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis. Translational Psychiatry, 11. 82. ISSN 2158-3188 doi: 10.1038/s41398-021-01201-4

Abstract/Summary

Attention-deficit/hyperactivity disorder (ADHD) affects 5% of children world-wide. Of these, two-thirds continue to have impairing symptoms of ADHD into adulthood. Although a large literature implicates structural brain differences of the disorder, it is not clear if adults with ADHD have similar neuroanatomical differences as those seen in children with recent reports from the large ENIGMA-ADHD consortium finding structural differences for children but not for adults. This paper uses deep learning neural network classification models to determine if there are neuroanatomical changes in the brains of children with ADHD that are also observed for adult ADHD, and vice versa. We found that structural MRI data can significantly separate ADHD from control participants for both children and adults. Consistent with the prior reports from ENIGMA-ADHD, prediction performance and effect sizes were better for the child than the adult samples. The model trained on adult samples significantly predicted ADHD in the child sample, suggesting that our model learned anatomical features that are common to ADHD in childhood and adulthood. These results support the continuity of ADHD’s brain differences from childhood to adulthood. In addition, our work demonstrates a novel use of neural network classification models to test hypotheses about developmental continuity.

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/97010
Identification Number/DOI 10.1038/s41398-021-01201-4
Refereed Yes
Divisions Interdisciplinary Research Centres (IDRCs) > Centre for Integrative Neuroscience and Neurodynamics (CINN)
Life Sciences > School of Psychology and Clinical Language Sciences > Department of Psychology
Life Sciences > School of Psychology and Clinical Language Sciences > Development
Life Sciences > School of Psychology and Clinical Language Sciences > Neuroscience
Life Sciences > School of Psychology and Clinical Language Sciences > Psychopathology and Affective Neuroscience
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