Circadian distribution of epileptiform discharges in epilepsy: Candidate mechanisms of variability

Author:

Marinelli IsabellaORCID,Walker Jamie J.,Seneviratne Udaya,D’Souza Wendyl,Cook Mark J.,Anderson Clare,Bagshaw Andrew P.,Lightman Stafford L.,Woldman Wessel,Terry John R.

Abstract

Epilepsy is a serious neurological disorder characterised by a tendency to have recurrent, spontaneous, seizures. Classically, seizures are assumed to occur at random. However, recent research has uncovered underlying rhythms both in seizures and in key signatures of epilepsy—so-called interictal epileptiform activity—with timescales that vary from hours and days through to months. Understanding the physiological mechanisms that determine these rhythmic patterns of epileptiform discharges remains an open question. Many people with epilepsy identify precipitants of their seizures, the most common of which include stress, sleep deprivation and fatigue. To quantify the impact of these physiological factors, we analysed 24-hour EEG recordings from a cohort of 107 people with idiopathic generalized epilepsy. We found two subgroups with distinct distributions of epileptiform discharges: one with highest incidence during sleep and the other during day-time. We interrogated these data using a mathematical model that describes the transitions between background and epileptiform activity in large-scale brain networks. This model was extended to include a time-dependent forcing term, where the excitability of nodes within the network could be modulated by other factors. We calibrated this forcing term using independently-collected human cortisol (the primary stress-responsive hormone characterised by circadian and ultradian patterns of secretion) data and sleep-staged EEG from healthy human participants. We found that either the dynamics of cortisol or sleep stage transition, or a combination of both, could explain most of the observed distributions of epileptiform discharges. Our findings provide conceptual evidence for the existence of underlying physiological drivers of rhythms of epileptiform discharges. These findings should motivate future research to explore these mechanisms in carefully designed experiments using animal models or people with epilepsy.

Funder

University of Birmingham Dynamic Investment Fund

Epilepsy Research UK

Engineering and Physical Sciences Research Council

National Institute for Health and Care Research

Medical Research Council

Publisher

Public Library of Science (PLoS)

Subject

Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics

Reference65 articles.

1. Duncan JS, Sander JW, Sisodiya SM, Walker MC. Adult epilepsy; 2006. Available from: https://pubmed.ncbi.nlm.nih.gov/16581409/.

2. WHO. Epilepsy; 2019.

3. The Neurobiology of Epilepsy;HE Scharfman;Current neurology and neuroscience reports,2007

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