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Circadian distribution of epileptiform discharges in epilepsy: Candidate mechanisms of variability.
Marinelli, Isabella; Walker, Jamie J; Seneviratne, Udaya; D'Souza, Wendyl; Cook, Mark J; Anderson, Clare; Bagshaw, Andrew P; Lightman, Stafford L; Woldman, Wessel; Terry, John R.
Afiliación
  • Marinelli I; Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom.
  • Walker JJ; EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom.
  • Seneviratne U; Department of Neurosciences, Monash Health, Clayton, Australia.
  • D'Souza W; Department of Neuroscience, St. Vincent's Hospital, University of Melbourne, Melbourne, Australia.
  • Cook MJ; Department of Medicine, St. Vincent's Hospital, University of Melbourne, Melbourne, Australia.
  • Anderson C; Department of Neuroscience, St. Vincent's Hospital, University of Melbourne, Melbourne, Australia.
  • Bagshaw AP; School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia.
  • Lightman SL; Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom.
  • Woldman W; Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom.
  • Terry JR; Bristol Medical School: Translational Health Sciences, University of Bristol, Bristol, United Kingdom.
PLoS Comput Biol ; 19(10): e1010508, 2023 10.
Article en En | MEDLINE | ID: mdl-37797040
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Epilepsia Generalizada / Epilepsia Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Epilepsia Generalizada / Epilepsia Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido