Abstract
Although multiple studies have reported structural deficits in multiple brain regions in attention-deficit hyperactivity disorder (ADHD), we do not yet know if these deficits reflect a more systematic disruption to the anatomical organization of large-scale brain networks. Here we used a graph theoretical approach to quantify anatomical organization in children and adolescents with ADHD. We generated anatomical networks based on covariance of gray matter volumes from 92 regions across the brain in children and adolescents with ADHD (n=34) and age- and sex-matched healthy controls (n=28). Using graph theory, we computed metrics that characterize both the global organization of anatomical networks (interconnectivity (clustering), integration (path length) and balance of global integration and localized segregation (small-worldness)) and their local nodal measures (participation (degree) and interaction (betweenness) within a network). Relative to Controls, ADHD participants exhibited altered global organization reflected in more clustering or network segregation. Locally, nodal degree and betweenness were increased in the subcortical amygdalae in ADHD, but reduced in cortical nodes in the anterior cingulate, posterior cingulate, mid temporal pole and rolandic operculum. In ADHD, anatomical networks were disrupted and reflected an emphasis on subcortical local connections centered around the amygdala, at the expense of cortical organization. Brains of children and adolescents with ADHD may be anatomically configured to respond impulsively to the automatic significance of stimulus input without having the neural organization to regulate and inhibit these responses. These findings provide a novel addition to our current understanding of the ADHD connectome.
Highlights
Attention-deficit hyperactivity disorder (ADHD) is the most prevalent developmental disorder, affecting 6–7% of schoolaged children and adolescents
The manner in which these regions behave within a network is crucial in understanding these symptoms and has led to the more recent view that ADHD may be best described in terms of aberrance in a number of large-scale functional brain networks such as the default mode network (DMN), ventral attention network (VAN), frontoparietal and limbic networks.[5]
Previous studies of graph theoretical analysis of whole-brain resting-state functional magnetic resonance imaging (MRI) data have reported that children and adolescents with ADHD exhibit higher local clustering and lower global efficiency compared with Controls
Summary
Attention-deficit hyperactivity disorder (ADHD) is the most prevalent developmental disorder, affecting 6–7% of schoolaged children and adolescents. Small-world and network efficiency measures describe the balance between information segregation and integration at the global level, while regionally specific properties such as nodal degree demonstrate the contribution of ‘hubs’ that facilitate integrative processes.[6] Previous studies of graph theoretical analysis of whole-brain resting-state functional magnetic resonance imaging (MRI) data have reported that children and adolescents with ADHD exhibit higher local clustering and lower global efficiency compared with Controls This suggests that children and adolescents with ADHD may have less-optimized topological organization, reflecting a maturational delay in formation of functional networks[7,8] (see Cao et al.[9] for a review including network-specific findings). Correspondence: Professor LM Williams, Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA 94305, USA
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