Objectives: Neuroimaging studies report altered resting-state functional connectivity in attention deficit/hyperactivity disorder (ADHD) across multiple brain systems. However, there is inconsistency among individual studies. Methods: We meta-analyzed seed-based resting state studies of ADHD connectivity within and between four established resting state brain networks (default mode, cognitive control, salience, affective/motivational) using Multilevel Kernel Density Analysis method. Results: Twenty studies with 944 ADHD patients and 1121 controls were included in the analysis. Compared to controls, ADHD was associated with disrupted within-default mode network (DMN) connectivityreduced in the core (i.e. posterior cingulate cortex seed) but elevated in the dorsal medial prefrontal cortex subsystem (i.e. temporal pole-inferior frontal gyrus). Connectivity was elevated between nodes in the cognitive control system. When the analysis was restricted to children and adolescents, additional reduced connectivity was detected between DMN and cognitive control and affective/motivational and salience networks. Conclusions: Our data are consistent with the hypothesis that paediatric ADHD is a DMN-dysconnectivity disorder with reduced connectivity both within the core DMN subsystem and between that system and a broad set of nodes in systems involved in cognition and motivation.
EEG biomarkers have become increasingly used to aid in diagnosis of attention-deficit/hyperactivity disorder (ADHD). Despite several studies suggesting that EEG theta/beta ratio may help discriminating ADHD from other disorders, the effect of medications on theta/beta ratio is not known. Forty-three children with ADHD that were evaluated with quantitative EEG before and after methylphenidate were included in the study. Theta/beta ratio, theta and beta powers for whole brain, central, and frontal areas were calculated. Theta/beta power decreased significantly after treatment; however, this change was largely due to an increase in beta power, rather than a fall in theta power. The results suggest that beta power is sensitive to medication effects, while theta power remains as a trait biomarker unaffected by medication status. The value of EEG biomarkers for monitoring neuropsychological performance and clinical status should be explored by future studies.
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