Machine Learning to Address the Enigma of Temporal Lobe Epilepsy Lateralization

Englot, Dario J.

doi:10.1177/15357597211047421

Cited by 1 publication

(1 citation statement)

References 11 publications

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“… 57 , 58 This is particularly true in patients with temporal lobe epilepsy, in whom fast propagation of epileptic activity or bilateral independent discharges can lead to unclear lateralization. 59 More generally, it is known that EEG has a low sensitivity to diagnose epilepsy, ranging from 25% to 56%. 60 Even long-term EEG monitoring identifies IEDs in only 57% of patients with epilepsy who had previously normal EEG, 61 which altogether calls for new biomarkers to be identified.…”

Section: Discussionmentioning

confidence: 99%

Asymmetry of sleep electrophysiological markers in patients with focal epilepsy

Sheybani

Mégevand

Roehri

et al. 2023

Brain Communications

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Sleep can modulate epileptic activities, but our knowledge of sleep perturbation by epilepsy remains sparse. Interestingly, epilepsy and sleep both present with defining electrophysiological features in the form of specific graphoelements on EEG. This raises the possibility to identify, within ongoing EEG activity, how epilepsy impacts and disrupts sleep. Here, we asked whether the presence of a lateralized epileptic focus interferes with the expression of the dominant electrophysiological hallmarks of sleep: slow oscillations, slow waves and spindles. To this aim, we conducted a cross-sectional study and analysed sleep recordings with surface EEG from 69 patients with focal epilepsy (age range at EEG: 17-61 years, 29 females, 34 left focal epilepsy). Comparing patients with left and right focal epilepsy, we assessed inter-hemispheric asymmetry of sleep slow oscillations power (delta range, 0.5-4 Hz), sleep slow wave density, amplitude, duration and slope; and spindle density, amplitude, duration as well as locking to slow oscillations. We found significantly different asymmetries in slow oscillation power (p < 0.01); slow wave amplitude (p < 0.05) and slope (p < 0.01); spindle density (p < 0.0001) and amplitude (p < 0.05). To confirm that these population-based differences reflect actual patient-by-patient differences, we then tested whether asymmetry of sleep features can classify laterality of the epileptic focus using a Decision Tree and a 5-folds cross-validation. We show that classification accuracy is above chance level (accuracy of 65%, standard deviation: 5%) and significantly outperforms a classification based on a randomization of epileptic lateralization (randomization data accuracy: 50%, standard deviation 7%, unpaired t-test, p < 0.0001). Importantly, we show that classification of epileptic lateralization by the canonical epileptic biomarker, i.e., interictal epileptic discharges, improves slightly but significantly when combined with electrophysiological hallmarks of physiological sleep (from 75% to 77%, p < 0.0001, one-way ANOVA + Sidak’s multiple comparisons test). Together, we establish that epilepsy is associated with inter-hemispheric perturbation of sleep-related activities and provide an in-depth multi-dimensional profile of the main sleep electrophysiological signatures in a large cohort of patients with focal epilepsy. We provide converging evidence that the underlying epileptic process interacts with the expression of sleep markers, in addition to triggering well-known pathological activities, such as interictal epileptic discharges.

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