Symptom-correlated brain regions in young adults with combined-type ADHD: their organization, variability, and relation to behavioral performance

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is a widely diagnosed psychiatric disorder of childhood that may continue to manifest itself during adulthood. Across adults and children, inattention appears to be the most developmentally stable symptomatology of ADHD. To determine the neural systems that may be linked to such symptoms, the association between brain activation in a group of young adults in the face of an attentional challenge (the Stroop task) and inattentive symptoms was examined with functional magnetic resonance imaging. The results implicated a broad array of brain regions that are linked to behaviors compromised in ADHD, including executive function/cognitive control (prefrontal cortex, dorsal striatum), reward and motivational circuitry (ventral striatum), and stimulus representation and timing (posterior cortex and cerebellum). Also implicating these regions as being important for the manifestation of ADHD symptoms, the variability in the size of the BOLD signal across individuals was significantly higher for the ADHD group than for the control group, and variability across the time series in individuals with ADHD was linked to symptom severity and behavioral performance. The results suggest that a diverse set of brain structures is linked to ADHD symptoms and that the variability of activation within these regions may contribute to compromised attentional control.

Fig. 1

Brain regions correlated with inattentive symptomatology across condition. 1 = middle frontal gyrus (MFG), 2 = putamen (Puta), 3 = nucleus accumbens (NAC), 4 = inferior frontal gyrus (IFG), 5 = medial orbital frontal cortex (mOFC), 6 = inferior temporal gyrus (ITG), 7 = cerebellum (Cereb), 8 = lateral inferior parietal (LIP), 9 = thalamus (Thal).

Fig. 2

Results of the discriminant analysis for BOLD signal variability. Receiver operating characteristic curves for the discriminant analysis indicating general fit of themodel.