P.204 Behavioural and neural correlates of response inhibition in disruptive behaviour disorders

Background: Disruptive behavior disorders (DBDs) are among the most commonly diagnosed disorders in childhood and adolescence with a prevalence ranging of 1% to 11% [1] . Attention-deficit/hyperactivity disorder (ADHD) is frequently comorbid with DBDs, with reported comorbidity rates ranging up to 30% [2 , 3] . While impaired response inhibition has been regarded as a primary deficit specific to ADHD [4 –8] , the relationship between response inhibition and DBDs independent from ADHD is less well established [4 , 5 , 9 –11] . Here, we investigated the behavioral and neural correlates of response inhibition in children and adolescents with DBD without comorbid ADHD (DBD −ADHD) and DBD with comorbid ADHD (DBD + ADHD) in comparison with healthy controls (HC). Method: Event-related fMRI were available for 83 subjects with DBDs (8-18 years old, 16 females and 67 males, 58 with DBD −ADHD and 25 with DBD + ADHD), and 65 agematched HC (26 females and 39 males) while performing a performance-adjusted stop-signal task [12] . The fMRI data were preprocessed following ICA-AROMA protocol [13] and the subject-level analyses were conducted using a general linear model in FSL FEAT [14] . In the group-level analysis, F-test was conducted to determine possible between-group differences while controlling for sex, age, IQ, and scanning site by using an FDR-corrected cluster significance threshold of p = 0.05 with Z > 2.3. For every participant, the mean parameter estimates for all clusters showing significant group differences were extracted, and pairwise comparisons were carried out in R [15] . The task outcomes of the stop-signal task between the groups were compared by ANCOVAs, with sex, age, IQ, and scanning site as covariates, in R. To control family-wise type I error rate, Bonferroni-Holm correction [16] was applied to all pairwise comparisons. Results: Compared to the controls, the DBD-groups showed greater variability in mean reaction time and the DBD −ADHD also made more omission errors during go trials, while the groups did not differ in terms of speed of inhibitory control. During successful inhibition versus go trials, the DBD + ADHD group demonstrated increased activation in the right superior parietal regions compared to the other two groups. During successful versus failed inhibition, relative to controls, right frontal hyperactivation was shared by the DBD-groups while the DBD + ADHD group showed increased activation in the right parietal and left superior parietal regions compared to the other two groups. Further, bilateral parietal activation in DBDs were found to be correlated with ADHD symptom counts. Conclusion: Given that the groups did not differ in terms of response inhibition-related behavioral performance, right frontal hyperactivation shared by the DBD-groups could be associated with deficient higher-order processing of sensory information mediating stimulus selection and attention in the DBD population. Moreover, bilateral parietal hyperactivation in the DBD + ADHD group and positive correlations between these activations and ADHD symptom counts in DBDs suggest the recruitment of more attentional resources to maintain task performance at the same level as the other groups. Therefore, considering additional hyperactivation observed in the participants with DBD and comorbid ADHD, it is crucial to screen for comorbid conditions and take into account ADHD comorbidity in treatment of DBDs [2–11]