Vagus nerve stimulation (VNS) is an established adjunctive therapy for drug-resistant epilepsy. Experimental and clinical evidence indicates that its therapeutic effects involve distributed brain networks and multiple neurochemical pathways. Electroencephalography (EEG) has been widely used to characterize VNS-related neurophysiological changes, including alterations in conventional oscillatory activity, functional connectivity, and, more recently, aperiodic spectral components such as the spectral exponent and spectral offset. However, these EEG findings are often interpreted without sufficient consideration of the neurochemical intermediates that may contribute to the observed electrophysiological changes. In this structured narrative review, primarily focused on epilepsy, we examine how VNS-related EEG findings can be interpreted in light of noradrenergic, serotonergic, cholinergic, GABAergic, and neurotrophic mechanisms. We also discuss methodological challenges in the analysis of periodic and aperiodic EEG components and outline how machine learning approaches and adaptive closed-loop neuromodulation strategies may support the development of clinically useful VNS biomarkers.
Muroni et al. (Tue,) studied this question.