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A two-state neuronal model with alternating exponential excitation

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dc.creatorRatanov, Nikita
dc.date.accessioned2020-05-25T23:56:55Z
dc.date.available2020-05-25T23:56:55Z
dc.date.created2019spa
dc.description.abstractWe develop a stochastic neural model based on point excitatory inputs. The nerve cell depolarisation is determined by a two-state point process corresponding the two states of the cell. The model presumes state-dependent excitatory stimuli amplitudes and decay rates of membrane potential. The state switches at each stimulus time. We analyse the neural firing time distribution and the mean firing time. The limit of the firing time at a definitive scaling condition is also obtained. The results are based on an analysis of the first crossing time of the depolarisation process through the firing threshold. The Laplace transform technique is widely used. © 2019 the author.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.3934/mbe.2019171
dc.identifier.issn15471063
dc.identifier.issn15510018
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/22559
dc.language.isoengspa
dc.publisherAmerican Institute of Mathematical Sciencesspa
dc.relation.citationEndPage3434
dc.relation.citationIssueNo. 5
dc.relation.citationStartPage3411
dc.relation.citationTitleMathematical Biosciences and Engineering
dc.relation.citationVolumeVol. 16
dc.relation.ispartofMathematical Biosciences and Engineering, ISSN:15471063, 15510018, Vol.16, No.5 (2019); pp. 3411-3434spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85064904101&doi=10.3934%2fmbe.2019171&partnerID=40&md5=c614b4f6e4aec6249e214460fc6a4b36spa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.keywordDecay (organic)spa
dc.subject.keywordDepolarizationspa
dc.subject.keywordExcited statesspa
dc.subject.keywordLaplace transformsspa
dc.subject.keywordNeuronsspa
dc.subject.keywordStochastic systemsspa
dc.subject.keywordTime switchesspa
dc.subject.keywordAsymptotical behaviourspa
dc.subject.keywordFirst passage timespa
dc.subject.keywordLaplace transform techniquesspa
dc.subject.keywordMembrane potentialsspa
dc.subject.keywordNeural activityspa
dc.subject.keywordNeural modelingspa
dc.subject.keywordNeuronal modelspa
dc.subject.keywordState-dependentspa
dc.subject.keywordStochastic modelsspa
dc.subject.keywordArticlespa
dc.subject.keywordDepolarizationspa
dc.subject.keywordExcitationspa
dc.subject.keywordLaplace transformspa
dc.subject.keywordMembrane potentialspa
dc.subject.keywordNerve cellspa
dc.subject.keywordProbabilityspa
dc.subject.keywordStochastic modelspa
dc.subject.keywordAsymptotical behaviourspa
dc.subject.keywordFiring probabilityspa
dc.subject.keywordFirst passage timespa
dc.subject.keywordJump-telegraph processspa
dc.subject.keywordNeural activityspa
dc.titleA two-state neuronal model with alternating exponential excitationspa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaArtículospa
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