Evidence from "big data" for the default-mode hypothesis of ADHD: a mega-analysis of multiple large samples

Abstract

We sought to identify resting-state characteristics related to attention deficit/hyperactivity disorder, both as a categorical diagnosis and as a trait feature, using large-scale samples which were processed according to a standardized pipeline. In categorical analyses, we considered 1301 subjects with diagnosed ADHD, contrasted against 1301 unaffected controls (total N = 2602; 1710 males (65.72%); mean age = 10.86 years, sd = 2.05). Cases and controls were 1:1 nearest neighbor matched on in-scanner motion and key demographic variables and drawn from multiple large cohorts. Associations between ADHD-traits and resting-state connectivity were also assessed in a large multi-cohort sample (N = 10,113). ADHD diagnosis was associated with less anticorrelation between the default mode and salience/ventral attention (B = 0.009, t = 3.45, p-FDR = 0.004, d = 0.14, 95% CI = 0.004, 0.014), somatomotor (B = 0.008, t = 3.49, p-FDR = 0.004, d = 0.14, 95% CI = 0.004, 0.013), and dorsal attention networks (B = 0.01, t = 4.28, p-FDR < 0.001, d = 0.17, 95% CI = 0.006, 0.015). These results were robust to sensitivity analyses considering comorbid internalizing problems, externalizing problems and psychostimulant medication. Similar findings were observed when examining ADHD traits, with the largest effect size observed for connectivity between the default mode network and the dorsal attention network (B = 0.0006, t = 5.57, p-FDR < 0.001, partial-r = 0.06, 95% CI = 0.0004, 0.0008). We report significant ADHD-related differences in interactions between the default mode network and task-positive networks, in line with default mode interference models of ADHD. Effect sizes (Cohen's d and partial-r, estimated from the mega-analytic models) were small, indicating subtle group differences. The overlap between the affected brain networks in the clinical and general population samples supports the notion of brain phenotypes operating along an ADHD continuum.

Fig. 1. Forest plots for brain network metrics that differed significantly (corrected p < 0.05) between N = 1301 ADHD cases and N = 1301 non-ADHD controls.

The top line shows the effect size (Cohen’s d) and corresponding 95% confidence intervals for the main mega-analytic model. The subsequent rows show the results of models performed within each cohort (NCR N = 122; HBN = 575; ADHD200-Peking N = 199; ADHD200-NYU N = 182; ABCD N = 1524). Panel (A) shows the results for connectivity between the default mode network and the dorsal attention network. Panel (B) shows the results for connectivity between the default mode network and the salience/ventral attention network. Panel (C) shows the results for connectivity between the default mode network and somatomotor network.

Fig. 2. Associations between ADHD diagnosis and connectivity within and between brain networks.

Red indicates a negative association. Blue indicates a positive association. Darker shades represent stronger associations. Effect sizes from the linear mixed models are presented for network connections significant at p < 0.05 after correction for multiple comparisons.

Fig. 3. Forest plots for significant associations (corrected p < 0.05) between ADHD-traits and resting-state connectivity (N = 10,113).

The top line shows the effect size (partial r) and corresponding 95% confidence intervals for the main mega-analytic model. The subsequent rows show the results of models performed within each cohort (NCR N = 100; NCANDA N = 504; HCP-D N = 494; HBN N = 692; ABCD N = 8323). Panel (A) shows the results for connectivity between the default mode network and the dorsal attention network. Panel (B) Shows the results for connectivity between the default mode network and the frontoparietal network. Panel (C) Shows the results for connectivity within the dorsal attention network. Panel (D) Shows the results for connectivity between the default mode network and the salience/ventral attention network. Panel (E) Shows the results for connectivity between the salience/ventral attention network and the somatomotor network. Panel (F) Shows the results for connectivity between the default mode network and the somatomotor network.