Channel block of the astrocyte network connections accounting for the dynamical transition of epileptic seizures

Channel block of the astrocyte network connections accounting for the dynamical transition of epileptic seizures | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Channel block of the astrocyte network connections accounting for the dynamical transition of epileptic seizures Jiajia Li, Jian Song, Ning Tan, Chenglong Cao, Mengmeng Du, Shengjun Xu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-231281/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Aug, 2021 Read the published version in Nonlinear Dynamics → Version 1 posted 4 You are reading this latest preprint version Abstract Epilepsy has been found to be modulated by the astrocyte systems in experiments, and tremendous modeling studies have unveiled the roles of astrocyte cellular functions such as the calcium and potassium channels in the epileptic seizures. However, little attention has been paid to the structure changes of astrocytes in the epileptic seizures in the scale of networks. This paper first constructs a neuron-astrocyte network model to explain the experimental observation that astrocytes mainly induce epilepsy by blocking the channels of the astrocyte gap junction in the network scale. Such model is used to discuss potential seizure induction process in the network by changing the connection intensity of the astrocyte gap junction. The simulation results show that a decrease of the gap junction intensity changes the firing pattern of the population of neurons from slow periodical firing to high-frequency epileptic seizures, featuring epileptic patterns of depolarization blocks. This further verifies that epileptic seizures are experimentally induced via the channel block of the astrocyte gap junctions. Because of the heterogeneous structure of the real neuron-astrocyte network, the effect of changing astrocyte network structures on the seizure activities is then studied in two typical network structures: the regular neighboring connection and the random connection. The results show that an increase of the number of regular connections of the regular neighboring astrocyte network could inhibit the induction and spread of the epileptic seizures. The epileptic inhibition can be achieved similarly by increasing the connection probability of the random astrocyte network. These findings further provide evidence for the experimental phenomena of the protective response of gliosis to epilepsy with increasing gap junctions. Above all, the simulation results suggest a potential pathway of epilepsy treatment by targeting the astrocyte gap junctions. Applied Mathematics dynamic transition epileptic seizures random networks gap junction inositol triphosphate Full Text Cite Share Download PDF Status: Published Journal Publication published 05 Aug, 2021 Read the published version in Nonlinear Dynamics → Version 1 posted Editorial decision: Accept 14 Jul, 2021 Reviews received at journal 09 Jun, 2021 Editor assigned by journal 09 Jun, 2021 First submitted to journal 08 Jun, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-231281","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":32476141,"identity":"f26669f7-1c6d-4171-bc65-ba257207c70a","order_by":0,"name":"Jiajia Li","email":"","orcid":"","institution":"Xi'an University of Architecture and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jiajia","middleName":"","lastName":"Li","suffix":""},{"id":32476142,"identity":"609aff3c-e2c7-45e6-a355-833329a4584c","order_by":1,"name":"Jian Song","email":"","orcid":"","institution":"Guangzhou Military Region Wuhan 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