Background Current clinical anesthesia monitors often utilize drug-invariant indices that simplify cortical dynamics, potentially overlooking pharmacological nuances. While Propofol and Sevoflurane are both GABAergic, they may induce distinct neural states. This study aimed to identify the divergent periodic and aperiodic EEG signatures that distinguish these two regimens during the steady-state maintenance phase. Methods A retrospective analysis was conducted using data from an open-access clinical database comprising 44 surgical patients (Propofol group, n = 27; Sevoflurane group, n = 17). EEG data were extracted during the pharmacological steady-state (20 min post-loss of consciousness to 10 min pre-end of surgery). Seventeen features, including relative band power, alpha peak frequency, and aperiodic components, were then derived. A multivariate statistical framework utilizing subject-independent cross-validation and SHapley Additive exPlanations (SHAP) analysis was implemented to identify and rank the most discriminatory biological markers. Results The multivariate model achieved high discriminatory performance with a rigorous subject-level accuracy of 91.43%. Relative theta power, theta-to-alpha ratio, and alpha peak frequency were identified as the primary differentiators, occupying the top tiers of the SHAP importance ranking. Specifically, the Sevoflurane group exhibited a distinct elevation in theta-band prominence and a significant downward shift in alpha peak frequency (8.78 Hz vs. 10.88 Hz for Propofol). Furthermore, the aperiodic exponent emerged as a critical discriminatory feature, demonstrating a significantly steeper background spectral slope under Sevoflurane (2.37 vs. 2.07 for Propofol, p = 0.039). Conversely, alpha bandwidth ( p = 0.263) and signal complexity measures (e.g., spectral entropy, p = 0.721) provided negligible discriminatory value. Conclusion Propofol and Sevoflurane maintain unconsciousness via distinct neurophysiological regimes. The differentiation between these two agents is primarily driven by structural oscillatory shifts, specifically theta-band prominence and alpha peak deceleration, along with steepened aperiodic background dynamics, rather than periodic bandwidth or overall signal complexity. These findings underscore the distinct cortical modulation patterns of different GABAergic anesthetics and support the development of agent-specific, multidimensional monitoring protocols to enhance precision in individualized brain state assessment.
Shen et al. (Tue,) studied this question.