Measuring the effects of sleep on epileptogenicity with multifrequency entropy. Issue 9 (September 2021) - Sathyanarayana, Aarti; El Atrache, Rima; Jackson, Michele; Alter, Aliza S.; Mandl, Kenneth D.; Loddenkemper, Tobias; Bosl, William J.
Highlights: Patients with Benign Epilepsy with Centrotemporal Spikes (BECTS) had lower multifrequency entropy (MSE) across all stages of sleep and wakefulness. Epileptic regions of the brain exhibit lower MSE patterns than the rest of the brain in epilepsy patients. MSE decreases during sleep, confirming an association between sleep, lower MSE, and increased likelihood of seizure. Abstract: Objective: We demonstrate that multifrequency entropy gives insight into the relationship between epileptogenicity and sleep, and forms the basis for an improved measure of medical assessment of sleep impairment in epilepsy patients. Methods: Multifrequency entropy was computed from electroencephalography measurements taken from 31 children with Benign Epilepsy with Centrotemporal Spikes and 31 non-epileptic controls while awake and during sleep. Values were compared in the epileptic zone and away from the epileptic zone in various sleep stages. Results: We find that (I) in lower frequencies, multifrequency entropy decreases during non-rapid eye movement sleep stages when compared with wakefulness in a general population of pediatric patients, (II) patients with Benign Epilepsy with Centrotemporal Spikes had lower multifrequency entropy across stages of sleep and wakefulness, and (III) the epileptic regions of the brain exhibit lower multifrequency entropy patterns than the rest of the brain in epilepsy patients. Conclusions: Our results show that multifrequency entropy decreases during sleep, particularly sleep stage 2, confirming, in a pediatric population, an association between sleep, lower multifrequency entropy, and increased likelihood of seizure. Significance: We observed a correlation between lowered multifrequency entropy and increased epileptogenicity that lays preliminary groundwork for the detection of a digital biomarker for epileptogenicity.