Reduced occurrence of alpha waves during resting state predicts high ADHD traits in young adults

Abstract

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition with significant cognitive and social impacts. Identifying reliable biomarkers for ADHD is crucial for developing personalized therapies. Electroencephalography (EEG) alpha oscillations (8-12 Hz) have been suggested as a potential biomarker, but findings have been inconsistent. This study aimed to investigate whether alpha oscillations in young adulthood are associated with high ADHD traits using EEG data from a large twin sample (N = 556) enriched with participants with ADHD and autism. We assessed whether alpha oscillations during rest were associated with high ADHD traits through logistic regression analysis. In addition, we used twin modelling to estimate the heritability of EEG alpha measures and their relationship with ADHD traits. Results showed that relative alpha power was a significant predictor of ADHD traits when controlling for other factors such as age, sex and autistic traits. Specifically, we found that for each unit decrease in relative alpha power, the likelihood of being in the high ADHD trait group increased by approximately 26%. Further analysis suggested that group differences were due to a reduced occurrence (but not amplitude) of oscillatory bursts in the alpha range. Finally, our twin modelling results suggested that although alpha power is heritable, the genetic factors contributing to individual differences in alpha measures and ADHD traits were largely independent. Together, these findings suggest that reduced alpha oscillations, particularly occurrence of alpha bursts, may serve as a potential biomarker for ADHD. Our results may have implications for neuromodulation therapies targeting alpha rhythms in ADHD, such as neurofeedback and transcranial alternating current stimulation (tACS).