Brain Connectivity Mediates Heartbeat-Evoked Potential Alterations between Children with ADHD and Comorbid ADHD-ASD.

Zhao, Jiajing; Yan, Chenyu; Bao, Mengyi; Zhou, Qing; Li, Haifeng; Pan, Gang; Yao, Lin; Wang, Yueming · IEEE Trans Biomed Eng · 2026

other · Level V

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Abstract

The comorbidity between Attention Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) is a complex, poorly understood phenomenon. This study investigates the neural mechanisms underlying this comorbidity through the lens of brain-heart interactions, integrating distinct physiological systems to elucidate potential pathophysiological differences. Resting-state EEG and ECG were recorded from 63 children with ADHD, 44 with comorbid ADHD-ASD, and an exploratory cohort of 23 with pure ASD. Heartbeat-Evoked Potentials (HEP) and Heartbeat-Induced Networks (HINs) were computed. Mediation analysis explored whether brain connectivity features mediate the observed HEP waveforms differences. Compared to the comorbid group, the ADHD group exhibited attenuated negative HEP amplitudes (150-200 ms post-R-peak). The comorbid group also demonstrated distinct characteristic path lengths in theta and alpha bands (eyes-open) and higher theta global efficiency (eyes-closed). Importantly, theta global efficiency mediated the group differences in HEP amplitudes (p=0.016). Exploratory analyses with the pure ASD cohort confirmed these alterations were comorbidity-specific and not strictly driven by ASD traits. This study reveals distinct resting-state brain-heart interaction patterns in children with pure ADHD compared to comorbid ADHD-ASD. The enhanced brain network efficiency observed in the comorbid group suggests the presence of distinct neural network reorganizations arising from the complex interaction of dual traits, providing neurophysiological evidence that challenges the simple additive model. By characterizing these divergent neural signatures, this work contributes to unraveling the complex mechanisms of comorbidity and highlights potential biomarkers for more precise clinical diagnosis and intervention.