Neural mass modelling reveals that hyperexcitability underpins slow-wave sleep changes in children with epilepsy

Abstract

ObjectiveThe relationship between sleep and epilepsy is important but imperfectly understood. We sought to understand why children with epilepsy have altered sleep homeostasis.MethodsWe used neural mass models to replicate sleep EEG recorded from 15 children with focal lesional epilepsies and 16 healthy age-matched controls.ResultsThe models revealed that sleep EEG differences are driven by enhanced firing rates in the neuronal populations of patients, which arise predominantly due to enhanced excitatory synaptic currents. These differences were more marked in patients who had seizures within 72 hours after the sleep recording. Furthermore, models inferred from patients resided closer in parameter space to models of a typical seizure rhythm.SignificanceThese results demonstrate that brain mechanisms relating to epilepsy manifest in the interictal EEG in slow-wave sleep, and that EEG recorded from patients can be mapped to synaptic deficits that may explain their predisposition to seizures. Neural mass models inferred from sleep EEG data have the potential to generate new biomarkers to predict seizure occurrence or inform treatment decisions.1.Key PointsThe mechanisms that differentiate children with epilepsy from controls during slow-wave sleep can be understood using a mathematical model.The observed spectral power shifts in patients are predominately explained by greater excitatory synaptic currents.These differences in currents place patients’ models closer to seizure rhythms.Ultimately, this framework could help foster the development of biomarkers to guide intervention in epilepsy.