Individual Alpha Frequency as an EEG Biomarker of Drug-Related Cognitive Burden in Epilepsy

Background: EEG alpha rhythm is well-proven to correlate with cognitive performance in healthy subjects. We aimed to evalu-ate the potential of EEG background activity, quantified as individual alpha frequency (IAF), as a biomarker of cognitive impair-ment induced by antiseizure medications (ASMs) in people with epilepsy (PwE).Methods: We conducted a cross-sectional study (S1) and a prospective longitudinal study (S2). In S1, PwE underwent EEGrecording and concurrent EpiTrack assessment. In S2, EEG and EpiTrack were performed before and 6 months after initiat-ing cenobamate. Correlation analyses assessed the association between EpiTrack scores and IAF (S1) and their changes post-cenobamate (S2). ANOVA and ANCOVA were used to compare IAF between cognitively impaired and unimpaired PwE. Logisticregression evaluated the incremental value of IAF combined with clinical variables to identify cognitive improvement followingASM modification.Results: We enrolled 100 PwE (42 ± 18 years) in S1 and 33 PwE (45 ± 15 years) in S2. IAF correlated significantly with EpiTrackscores in S1 (R = 0.21, p = 0.03), and IAF changes mirrored EpiTrack improvements post-cenobamate in S2 (R = 0.34, p = 0.04).Cognitively impaired PwE displayed significantly lower IAF independent of age, seizure frequency, epileptiform activity, andpharmacological load (p = 0.01–0.005). Adding IAF to clinical variables significantly improved the logistic model's accuracy inpredicting cognitive improvement post-treatment (AUC: 0.83 ± 0.04 vs. 0.71 ± 0.04, p = 0.005).Conclusions: EEG background activity, assessed via IAF, is sensitive to cognitive impairment related to ASMs in PwE, demon-strated in both cross-sectional and longitudinal contexts. IAF is thus a promising, simple, cost-effective biomarker to monitorcognitive burden in clinical epilepsy management.