Background: Task-based functional magnetic resonance imaging (fMRI) studies of adult attention-deficit/hyperactivity disorder (ADHD) have revealed various ADHD-related dysfunctional brain regions, with heterogeneous findings across studies. Here, we used novel meta-analytic data-driven approaches to characterize the function and connectivity profile of ADHD-related dysfunctional regions consistently detected across studies.
Methods: We first conducted an activation likelihood estimation meta-analysis of 24 task-based fMRI studies in adults with ADHD. Each ADHD-related dysfunctional region resulting from the activation likelihood estimation meta-analysis was then analyzed using functional decoding based on ~7500 fMRI experiments in the BrainMap database. This approach allows mapping brain regions to functions not necessarily tested in individual studies, thus suggesting possible novel functions for those regions. Additionally, ADHD-related dysfunctional regions were clustered based on their functional coactivation profiles across all the experiments stored in BrainMap (meta-analytic connectivity modeling).
Results: ADHD-related hypoactivation was found in the left putamen, left inferior frontal gyrus (pars opercularis), left temporal pole, and right caudate. Functional decoding mapped the left putamen to cognitive aspects of music perception/reproduction and the left temporal lobe to language semantics; both these regions clustered together on the basis of their meta-analytic functional connectivity. Left inferior gyrus mapped to executive function tasks; right caudate mapped to both executive function tasks and music-related processes.
Conclusions: Our study provides meta-analytic support to the hypothesis that, in addition to well-known deficits in typical executive functions, impairment in processes related to music perception/reproduction and language semantics may be involved in the pathophysiology of adult ADHD.
Keywords: Adults; Attention-deficit/hyperactivity disorder; Functional decoding; Meta-analysis; Meta-analytic connectivity modeling; fMRI.
Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.