Abstract / Summary
Etomidate, a short-acting GABA_A receptor modulator and emerging novel psychoactive substance, is increasingly abused non-medically. Despite rising clinical concern, the neuropsychological profiles of etomidate use disorder (EUD) remain poorly characterized, prompting this systematic investigation of its clinical and neurophysiological features. 152 individuals with EUD and 67 age-matched healthy controls (HC) were recruited. Participants completed a series of standardized assessments measuring craving, impulsivity, inhibitory control, and habitual behavior. Resting-state EEG data were analyzed using microstate analysis to characterize the temporal organization of large-scale brain activity, and a multidimensional feature-based support vector machine (SVM) model was built to distinguish EUD from HC. The EUD group exhibited significantly higher craving and impulsivity, and poorer performance on stop-signal and reversal learning tasks. Microstate analysis revealed significantly longer durations of microstates B, C, and D and reduced occurrence of microstate A in the EUD group. SVM classification achieved an AUC of 0.777. This is the first comprehensive characterization of EUD, demonstrating distinct clinical features and alterations in the temporal organization of large-scale brain activity. These findings characterize cross-sectional clinical and neurophysiological features associated with EUD and highlight the potential value of EEG microstate analysis to probe such brain network temporal changes.