Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder

Fig. 1. Children with ADHD-C exhibited hyper-connectivity in the anterior default mode network (aDMN) compared to age-match healthy controls (HC). A. Brain slice highlighting the region showing greater functional connectivity (in red) within the anterior default network (in yellow) in ADHD-C group than HC group (p < .05 FWE corrected). In contrast, ADHD-I did not differ in intra-network connectivity from HC. B. The mean functional connectivity values across all voxels in the peak region highlighted in panel A was plotted for the three groups. Error bars indicate standard error. * represents FWE corrected p < .05.

Fig. 2. Loss of between-network functional segregation in ADHD and its association with symptom severity. Row 1: Brain slices showing the spatial maps of the two network components. Row 2: Compared to controls, ADHD had higher functional connectivity between the left ECN and the salience network (full correlation, panel A), between subcortical and visual networks (partial correlation, panel B) and between the posterior DMN and left auditory network (partial correlation, panel C). The bars and error bars indicate mean and standard error respectively. * represents p < .05 FWE corrected for all the pairs between all the ICs of interest. Row 3: The loss of between network functional segregation related to symptom severity in ADHD participants including CBCL attention-deficit/hyperactivity problems (A & B) and CBCL internalizing problems (C) (red: ADHD inattentive subtype (ADHD-I); blue: ADHD combined subtype (ADHD-C)). Abbreviations: ECN: executive control network; SN: salience network; DMN: default mode network.

Fig. 3. Differential degree of between-network hyper-connectivity in ADHD combined (ADHD-C) and inattentive (ADHD-I) subtypes. Row 1: Brain slices showing the spatial maps of the two network components. Row 2: Compared to controls, ADHD-C had higher functional connectivity between left ECN and the salience network (full correlation, panel A), between subcortical and visual network (partial correlation, panel B) and between posterior DMN and left auditory network (full correlation, panel C; partial correlation, panel D). The bars and error bars indicate mean and standard error respectively. * represents p < .05 FWE corrected for all the pairs between all the ICs of interest.

Fig. 4. Children with ADHD showed lower brain network modularity compared to healthy controls (HCs). (A) ADHD group had lower network modularity scores. The horizontal axis represents a range of γ values (i.e., multiple resolution levels) for the community partition algorithm. Data were reported as mean values and standard errors (* indicates p < .05, p = .033, .039, .042, .031, .031, .030 for γ = 1 to 6 respectively). (B) Children with ADHD combined subtype (ADHD-C) but not children with ADHD inattentive subtype (ADHD-I) had reduced modularity compared with controls (* indicates p < .05, p = .019, .021, .025, .019, .015, .021 for γ = 1 to 6 respectively). C. Lower modularity scores were associated with more CBCL internalizing problems in subjects with ADHD across almost all γ values (γ = 2 presented here as an example).