| Literature DB >> 33462190 |
Max M Owens1, Nicholas Allgaier2, Sage Hahn2, DeKang Yuan2, Matthew Albaugh2, Shana Adise2, Bader Chaarani2, Joseph Ortigara2, Anthony Juliano2, Alexandra Potter2, Hugh Garavan2.
Abstract
Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R2 = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R2 = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task.Entities:
Year: 2021 PMID: 33462190 PMCID: PMC7813832 DOI: 10.1038/s41398-020-01192-8
Source DB: PubMed Journal: Transl Psychiatry ISSN: 2158-3188 Impact factor: 6.222