Resting-state EEG functional connectivity predicts autistic traits in typically developing individuals

The dimensional approach to autism spectrum disorder (ASD) considers ASD as the extreme of a dimension traversing through the general population, with autistic traits continuously distributed across the general population. Yet, their neurophysiological correlates in typically developing (TD) individuals remain underexplored. This study examines the associations between autistic traits, as measured by the autism spectrum quotient (AQ), and electroencephalogram (EEG) functional connectivity (FC) abnormalities in nonclinical populations. Resting-state EEG data were collected from 88 TD adults (43 males, 45 females; mean age 24.43 ± 5.61). To evaluate large-scale brain dynamics, 88 neurotypical subjects were measured across five frequency bands for FC metrics, including phase locking value (PLV), weighted phase lag index (WPLI), and phase lag index (PLI). We conducted multiple regression analyses between the AQ and FC across all EEG frequency bands, followed by Pearson correlations to examine the relationships between specific FC features and individual AQ subscales. Regression analyses revealed that the Delta/Theta band, particularly in PLV connectivity, significantly predicted autistic traits (FDR corrected p = 0.010 for both), with lower connectivity associated with greater autistic trait expression. Additionally, EEG Theta/Delta band PLV connectivity metrics revealed significant correlations with social skills and communication AQ subscales, core domains affected in ASD. Our findings demonstrate that EEG FC in low-frequency bands (Delta/Theta), specifically PLV connectivity, is associated with autistic traits in the general population, with correlation analyses revealing specific links to the social skills and communication AQ subscales. These results highlight Delta/Theta PLV connectivity as a sensitive physiological correlate of autistic trait expression in TD children.