Intrinsic functional connectivity alterations in medication-naïve children with combined and inattentive ADHD types: Evidence from cortical surface-based analysis.

BACKGROUND

While brain network dysfunction characterizes attention-deficit/hyperactivity disorder (ADHD), surface-based connectivity patterns underlying its clinical heterogeneity remain underexplored. Herein, we investigated surface-based complex network architecture alterations in medication-naïve children with combined (ADHD-C) and inattentive (ADHD-I) subtypes.

METHODS

Children with ADHD-C (n = 43), ADHD-I (n = 35), and healthy controls (HCs; n = 31) were recruited for a series of clinical examinations and resting-state fMRI. We utilized surface-based graph theoretical analysis (GTA) and functional connectivity (FC) to assess network topology, correlating imaging indices with clinical variables.

RESULTS

Significant intra- and inter-network FC disruptions emerged in children with ADHD, particularly in default mode (DMN), ventral attentional (VAN), and somatosensory-motor (SMN) networks. In particular, the ADHD-C group (vs HC) exhibited more FC abnormalities involving SMN and DMN, whereas the ADHD-I group (vs HC) showed slightly more abnormal FC between VAN and dorsal attentional network (DAN). Crucially, ADHD-C patients demonstrated significantly weaker intra-SMN and SMN-DMN connectivity than the ADHD-I group. Generally, children with ADHD showed diminished global modularity, assortativity, and disrupted left lateral prefrontal cortex (PFCl1_L) nodal centrality. Additionally, higher FRCQ scores were significantly associated with increased assortativity in ADHD. The hypo-connectivity linking the DMN (Default-PFC7_L) and SMN (SomMot27_L) was correlated with both higher SNAP-IV Hyperactivity/Impulsivity and Total scores.

CONCLUSION

These findings elucidate neural substrates associated with sensorimotor and attentional deficits across ADHD subtypes. Surface-based network profiling underscores the disorder's biological heterogeneity and advances the mechanistic understanding of its complex neurodevelopment.