Computational Modeling of Attentional Impairments in Disruptive Mood Dysregulation and Attention Deficit/Hyperactivity Disorder.

Abstract Objective Computational models provide information about cognitive components underlying behavior. When applied to psychopathology-relevant processes, they offer additional insight to observed differences in behavioral performance. Drift diffusion models have been successfully applied to investigate processing efficiency during binary choice tasks. Using these models, we examine the association between psychopathology (irritability and inattention/hyperactivity) and processing efficiency under different attentional demands. Method N=187 youth with ADHD, DMDD, both disorders, or no major psychopathology (age M=13.09 years, SD=2.55; 34% female) completed an Eriksen Flanker task. Of these, 87 youth provided complete data on dimensional measures of the core symptom of DMDD (irritability) and those of ADHD, inattention and hyperactivity. Results In a categorical diagnosis-based analysis (N=187), we found significant interactive effects between ADHD, DMDD, and task condition on processing efficiency, whereby changes in processing efficiency between conflict and non-conflict conditions were larger in youth without psychopathology relative to patients. Analysis of symptom severity (n=87) across diagnosis similarly revealed an interaction between symptom dimensions and task condition on processing efficiency. Irritability moderated the magnitude of association between inattention symptoms and difference in processing efficiency between conflict and non-conflict conditions. Conclusion Adapting processing efficiency to cognitive demands may represent a shared cognitive endophenotype for both ADHD and DMDD. Highly irritable and/or inattentive youth may have difficulty adjusting processing efficiency to changing task demands possibly reflecting impairments in cognitive flexibility.