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dc.contributor.authorMarinelli, I
dc.contributor.authorWalker, JJ
dc.contributor.authorSeneviratne, U
dc.contributor.authorD'Souza, W
dc.contributor.authorCook, MJ
dc.contributor.authorAnderson, C
dc.contributor.authorBagshaw, AP
dc.contributor.authorLightman, SL
dc.contributor.authorWoldman, W
dc.contributor.authorTerry, JR
dc.date.accessioned2024-01-15T17:08:36Z
dc.date.issued2023-10-05
dc.date.updated2024-01-15T15:43:03Z
dc.description.abstractEpilepsy 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.en_GB
dc.description.sponsorshipUniversity of Birmingham Dynamic Investment Funden_GB
dc.description.sponsorshipEpilepsy Research UKen_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.description.sponsorshipNational Institute for Health and Care Research (NIHR)en_GB
dc.description.sponsorshipMedical Research Council (MRC)en_GB
dc.format.extente1010508-
dc.format.mediumElectronic-eCollection
dc.identifier.citationVol. 19(10), article e1010508en_GB
dc.identifier.doihttps://doi.org/10.1371/journal.pcbi.1010508
dc.identifier.grantnumberF2002en_GB
dc.identifier.grantnumberEP/T027703/1en_GB
dc.identifier.grantnumberAI01646en_GB
dc.identifier.grantnumberMR/N008936/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/135029
dc.identifierORCID: 0000-0002-1952-8759 (Walker, Jamie J)
dc.language.isoenen_GB
dc.publisherPublic Library of Science (PLoS)en_GB
dc.relation.urlhttps://github.com/imarinelli/Marinelli_PLOSCB2022en_GB
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pubmed/37797040en_GB
dc.rights© 2023 Marinelli et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_GB
dc.titleCircadian distribution of epileptiform discharges in epilepsy: Candidate mechanisms of variabilityen_GB
dc.typeArticleen_GB
dc.date.available2024-01-15T17:08:36Z
dc.contributor.editorBaud, M
dc.identifier.issn1553-734X
exeter.article-numberARTN e1010508
exeter.place-of-publicationUnited States
dc.descriptionThis is the final version. Available on open access from Public Library of Science via the DOI in this recorden_GB
dc.descriptionData Availability: All code used to produce the results presented in this manuscript are available on GitHub at https://github.com/imarinelli/Marinelli_PLOSCB2022en_GB
dc.identifier.eissn1553-7358
dc.identifier.journalPLoS Computational Biologyen_GB
dc.relation.ispartofPLoS Comput Biol, 19(10)
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2023-09-10
dc.rights.licenseCC BY
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2023-10-05
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2024-01-15T17:06:00Z
refterms.versionFCDVoR
refterms.dateFOA2024-01-15T17:08:41Z
refterms.panelBen_GB
refterms.dateFirstOnline2023-10-05


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