Multistability and stochastic dynamics of Rulkov neurons coupled via a chemical synapse
Электронный научный архив УРФУ
Информация об архиве | Просмотр оригинала| Поле | Значение | |
| Заглавие |
Multistability and stochastic dynamics of Rulkov neurons coupled via a chemical synapse
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| Автор |
Bashkirtseva, I.
Pisarchik, A. N. Ryashko, L. |
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| Тематика |
CHAOS
CHEMICAL SYNAPSE MAP-BASED NEURON MODELS NEURONAL DYNAMICS NOISE-INDUCED EFFECTS STOCHASTIC SENSITIVITY SYNCHRONIZATION DYNAMICS NEURONS NUMERICAL METHODS STOCHASTIC MODELS STOCHASTIC SYSTEMS CHEMICAL SYNAPSE COUPLING STRENGTHS IN-PHASE MAP-BASED NEURON MODEL MULTISTABILITY NEURON MODELING NEURONAL DYNAMICS NOISE-INDUCED EFFECT STOCHASTIC SENSITIVITY STOCHASTICS SYNCHRONIZATION |
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| Описание |
We study complex dynamics of two Rulkov neurons unidirectionally connected via a chemical synapse with respect to three control parameters: (i) a parameter responsible for the type of dynamical behavior of a solitary neuron, (ii) coupling strength, and (iii) noise intensity. The coupled system exhibits various scenarios on the route from a stable equilibrium to chaos with respect to the coupling strength. We observe a variety of dynamical regimes, including mono-, bi- and tri-stability, order-chaos transitions and vice versa, as well as the coexistence of in-phase and anti-phase synchronization. We also study transitions between in-phase and out-of-phase synchronization with statistics on the duration of synchronization intervals and transitions from order to chaos. In addition to numerical simulations, we demonstrate the effectiveness of the analytical confidence ellipses method based on stochastic sensitivity approach. © 2023 The Author(s)
Russian Science Foundation, RSF: 21-11-00062 The work was supported by the Russian Science Foundation (project No. 21-11-00062). |
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| Дата |
2024-04-05T16:27:17Z
2024-04-05T16:27:17Z 2023 |
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| Тип |
Article
Journal article (info:eu-repo/semantics/article) |info:eu-repo/semantics/publishedVersion |
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| Идентификатор |
Bashkirtseva, I, Pisarchik, AN & Ryashko, L 2023, 'Multistability and stochastic dynamics of Rulkov neurons coupled via a chemical synapse', Communications in Nonlinear Science and Numerical Simulation, Том. 125, 107383. https://doi.org/10.1016/j.cnsns.2023.107383
Bashkirtseva, I., Pisarchik, A. N., & Ryashko, L. (2023). Multistability and stochastic dynamics of Rulkov neurons coupled via a chemical synapse. Communications in Nonlinear Science and Numerical Simulation, 125, [107383]. https://doi.org/10.1016/j.cnsns.2023.107383 1007-5704 Final All Open Access, Hybrid Gold https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163986624&doi=10.1016%2fj.cnsns.2023.107383&partnerID=40&md5=124dd290ecbbb134d6e714232e02c744 https://doi.org/10.1016/j.cnsns.2023.107383 http://elar.urfu.ru/handle/10995/130611 10.1016/j.cnsns.2023.107383 85163986624 001029016100001 |
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| Язык |
en
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| Связанные ресурсы |
info:eu-repo/grantAgreement/RSF//21-11-00062
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| Права |
Open access (info:eu-repo/semantics/openAccess)
cc-by-nc-nd https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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| Формат |
application/pdf
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| Издатель |
Elsevier B.V.
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| Источник |
Communications in Nonlinear Science and Numerical Simulation
Communications in Nonlinear Science and Numerical Simulation |
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