Attention deficit/hyperactivity disorder (ADHD) is increasingly being viewed as a dysfunction of distributed brain networks rather than focal abnormalities. Here we investigated the structural brain network differences in children and adolescents with ADHD and healthy controls, using graph theory metrics to describe the anatomic networks and connectivity patterns, and the Network Based Statistic (NBS) to isolate the network components that differ between the two groups. Using DWI high-angular resolution diffusion imaging (‘HARDI’), whole brain tractography was conducted on 21 ADHD-combined type boys (m 13.3 ± 1.9 yrs) and 21 typically developing boys (m 14.8 ± 2.1 yrs). This study presents a comprehensive structural network investigation in ADHD covering a range of commonly used methodologies, including both streamline and probabilistic tractography, tensor and constrained spherical deconvolution (CSD) models, as well as different edge weighting methods at a range of densities and t-thresholds. Using graph metrics, ADHD was associated with local neighbourhoods that were more modular and interconnected than controls, where there was a decrease in the global, long-range connections, indicating reduced communication between local, specialised networks in ADHD. ADHD presented with a sub-network of stronger connectivity encompassing bilateral frontostriatal connections as well as left occipital, temporal, and parietal regions, of which the white matter microstructure was associated with ADHD symptom severity. Probabilistic tractography using CSD and the Hagmann weighting method produced that highest stability and most robust network differences across t-thresholds. It demonstrates topological organisation disruption in distributed neural networks in ADHD, supportive of the theory of maturation delay in ADHD.
- Graph theory