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

EEG alpha rhythm is well-proven to correlate with cognitive performance in healthy subjects. We aimed to evaluate the potential of EEG background activity, quantified as individual alpha frequency (IAF), as a biomarker of cognitive impairment induced by antiseizure medications (ASMs) in people with epilepsy (PwE).

We conducted a cross-sectional study (S1) and a prospective longitudinal study (S2). In S1, PwE underwent EEG recording and concurrent EpiTrack assessment. In S2, EEG and EpiTrack were performed before and 6 months after initiating 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. Logistic regression evaluated the incremental value of IAF combined with clinical variables to identify cognitive improvement following ASM modification.

We enrolled 100 PwE (42 ± 18 years) in S1 and 33 PwE (45 ± 15 years) in S2. IAF correlated significantly with EpiTrack scores 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, and pharmacological load (p = 0.01-0.005). Adding IAF to clinical variables significantly improved the logistic model's accuracy in predicting cognitive improvement post-treatment (AUC: 0.83 ± 0.04 vs. 0.71 ± 0.04, p = 0.005).

EEG background activity, assessed via IAF, is sensitive to cognitive impairment related to ASMs in PwE, demonstrated in both cross-sectional and longitudinal contexts. IAF is thus a promising, simple, cost-effective biomarker to monitor cognitive burden in clinical epilepsy management.