Robust closed-loop control of spike-and-wave discharges in a thalamocortical computational model of absence epilepsy
In this paper, we investigate the abatement of spike-and-wave discharges in a thalamocortical model using a closed-loop brain stimulation method. We first explore the complex states and various transitions in the thalamocortical computational model of absence epilepsy by using bifurcation analysis....
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description | In this paper, we investigate the abatement of spike-and-wave discharges in a thalamocortical model using a closed-loop brain stimulation method. We first explore the complex states and various transitions in the thalamocortical computational model of absence epilepsy by using bifurcation analysis. We demonstrate that the Hopf and double cycle bifurcations are the key dynamical mechanisms of the experimental observed bidirectional communications during absence seizures through top-down cortical excitation and thalamic feedforward inhibition. Then, we formulate the abatement of epileptic seizures to a closed-loop tracking control problem. Finally, we propose a neural network based sliding mode feedback control system to drive the dynamics of pathological cortical area to track the desired normal background activities. The control system is robust to uncertainties and disturbances, and its stability is guaranteed by Lyapunov stability theorem. Our results suggest that the seizure abatement can be modeled as a tracking control problem and solved by a robust closed-loop control method, which provides a promising brain stimulation strategy. |
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We first explore the complex states and various transitions in the thalamocortical computational model of absence epilepsy by using bifurcation analysis. We demonstrate that the Hopf and double cycle bifurcations are the key dynamical mechanisms of the experimental observed bidirectional communications during absence seizures through top-down cortical excitation and thalamic feedforward inhibition. Then, we formulate the abatement of epileptic seizures to a closed-loop tracking control problem. Finally, we propose a neural network based sliding mode feedback control system to drive the dynamics of pathological cortical area to track the desired normal background activities. The control system is robust to uncertainties and disturbances, and its stability is guaranteed by Lyapunov stability theorem. Our results suggest that the seizure abatement can be modeled as a tracking control problem and solved by a robust closed-loop control method, which provides a promising brain stimulation strategy.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-019-45639-5</identifier><identifier>PMID: 31235838</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/378/116/2393 ; 631/378/1689/178 ; Cerebral cortex ; Cerebral Cortex - physiopathology ; Computational neuroscience ; Control systems ; Convulsions & seizures ; Electroencephalography ; Epilepsy ; Epilepsy, Absence - physiopathology ; Firing pattern ; Humanities and Social Sciences ; Humans ; Models, Neurological ; multidisciplinary ; Neural networks ; Science ; Science (multidisciplinary) ; Seizures ; Thalamus ; Thalamus - physiopathology</subject><ispartof>Scientific reports, 2019-06, Vol.9 (1), p.9093-16, Article 9093</ispartof><rights>The Author(s) 2019</rights><rights>2019. 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We first explore the complex states and various transitions in the thalamocortical computational model of absence epilepsy by using bifurcation analysis. We demonstrate that the Hopf and double cycle bifurcations are the key dynamical mechanisms of the experimental observed bidirectional communications during absence seizures through top-down cortical excitation and thalamic feedforward inhibition. Then, we formulate the abatement of epileptic seizures to a closed-loop tracking control problem. Finally, we propose a neural network based sliding mode feedback control system to drive the dynamics of pathological cortical area to track the desired normal background activities. The control system is robust to uncertainties and disturbances, and its stability is guaranteed by Lyapunov stability theorem. Our results suggest that the seizure abatement can be modeled as a tracking control problem and solved by a robust closed-loop control method, which provides a promising brain stimulation strategy.</description><subject>631/378/116/2393</subject><subject>631/378/1689/178</subject><subject>Cerebral cortex</subject><subject>Cerebral Cortex - physiopathology</subject><subject>Computational neuroscience</subject><subject>Control systems</subject><subject>Convulsions & seizures</subject><subject>Electroencephalography</subject><subject>Epilepsy</subject><subject>Epilepsy, Absence - physiopathology</subject><subject>Firing pattern</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>Models, Neurological</subject><subject>multidisciplinary</subject><subject>Neural networks</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><subject>Seizures</subject><subject>Thalamus</subject><subject>Thalamus - physiopathology</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kctu1TAQhiMEolXpC7BAltiwMfia2BskVHGpVAkJwdqaOJNzUpw42Emrvj3uSWkLC7wZW_PN75n5q-olZ285k-ZdVlxbQxm3VOlaWqqfVMeCKU2FFOLpo_tRdZrzJStHC6u4fV4dSS6kNtIcV8u32K55IT7EjB0NMc7Ex2lJMZDYkzwPP5HC1NFruELSDdnvIe0wk2EiQJY9BBijj2kZPIRSOc7rAssQp_IaY4cHFWgzTh4JzkPAOd-8qJ71EDKe3sWT6senj9_PvtCLr5_Pzz5cUK8atVDBvDK81aZHphRaIeqmE02rGm468Lq13EKPXiijut7wvqtlD-CtbaQE08uT6v2mO6_tiJ3HMhcEN6dhhHTjIgzu78w07N0uXrlaWy60LgJv7gRS_LViXtxYNoAhwIRxzU4IVVtWywP6-h_0Mq6prGGjhGS6bgolNsqnmHPC_r4Zztytr27z1RVf3cFXdyv96vEY9yV_XCyA3IBcUtMO08Pf_5H9DbO6sJ8</recordid><startdate>20190624</startdate><enddate>20190624</enddate><creator>Ge, Yafang</creator><creator>Cao, Yuzhen</creator><creator>Yi, Guosheng</creator><creator>Han, Chunxiao</creator><creator>Qin, Yingmei</creator><creator>Wang, Jiang</creator><creator>Che, Yanqiu</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-5988-7908</orcidid></search><sort><creationdate>20190624</creationdate><title>Robust closed-loop control of spike-and-wave discharges in a thalamocortical computational model of absence epilepsy</title><author>Ge, Yafang ; Cao, Yuzhen ; Yi, Guosheng ; Han, Chunxiao ; Qin, Yingmei ; Wang, Jiang ; Che, Yanqiu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-20c481b58fe044e92267d27b4718dac5b919afec2484df81fd63faac99733a8f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>631/378/116/2393</topic><topic>631/378/1689/178</topic><topic>Cerebral cortex</topic><topic>Cerebral Cortex - physiopathology</topic><topic>Computational neuroscience</topic><topic>Control systems</topic><topic>Convulsions & seizures</topic><topic>Electroencephalography</topic><topic>Epilepsy</topic><topic>Epilepsy, Absence - physiopathology</topic><topic>Firing pattern</topic><topic>Humanities and Social Sciences</topic><topic>Humans</topic><topic>Models, Neurological</topic><topic>multidisciplinary</topic><topic>Neural networks</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><topic>Seizures</topic><topic>Thalamus</topic><topic>Thalamus - physiopathology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ge, Yafang</creatorcontrib><creatorcontrib>Cao, Yuzhen</creatorcontrib><creatorcontrib>Yi, Guosheng</creatorcontrib><creatorcontrib>Han, Chunxiao</creatorcontrib><creatorcontrib>Qin, Yingmei</creatorcontrib><creatorcontrib>Wang, Jiang</creatorcontrib><creatorcontrib>Che, Yanqiu</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ge, Yafang</au><au>Cao, Yuzhen</au><au>Yi, Guosheng</au><au>Han, Chunxiao</au><au>Qin, Yingmei</au><au>Wang, Jiang</au><au>Che, Yanqiu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Robust closed-loop control of spike-and-wave discharges in a thalamocortical computational model of absence epilepsy</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2019-06-24</date><risdate>2019</risdate><volume>9</volume><issue>1</issue><spage>9093</spage><epage>16</epage><pages>9093-16</pages><artnum>9093</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>In this paper, we investigate the abatement of spike-and-wave discharges in a thalamocortical model using a closed-loop brain stimulation method. We first explore the complex states and various transitions in the thalamocortical computational model of absence epilepsy by using bifurcation analysis. We demonstrate that the Hopf and double cycle bifurcations are the key dynamical mechanisms of the experimental observed bidirectional communications during absence seizures through top-down cortical excitation and thalamic feedforward inhibition. Then, we formulate the abatement of epileptic seizures to a closed-loop tracking control problem. Finally, we propose a neural network based sliding mode feedback control system to drive the dynamics of pathological cortical area to track the desired normal background activities. The control system is robust to uncertainties and disturbances, and its stability is guaranteed by Lyapunov stability theorem. Our results suggest that the seizure abatement can be modeled as a tracking control problem and solved by a robust closed-loop control method, which provides a promising brain stimulation strategy.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>31235838</pmid><doi>10.1038/s41598-019-45639-5</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0002-5988-7908</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | 631/378/116/2393 631/378/1689/178 Cerebral cortex Cerebral Cortex - physiopathology Computational neuroscience Control systems Convulsions & seizures Electroencephalography Epilepsy Epilepsy, Absence - physiopathology Firing pattern Humanities and Social Sciences Humans Models, Neurological multidisciplinary Neural networks Science Science (multidisciplinary) Seizures Thalamus Thalamus - physiopathology |
title | Robust closed-loop control of spike-and-wave discharges in a thalamocortical computational model of absence epilepsy |
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