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Coexisting Attractors and Multistate Noise-Induced Intermittency in a Cycle Ring of Rulkov Neurons. / Bashkirtseva, Irina A.; Pisarchik, Alexander N.; Ryashko, Lev B.
In: Mathematics, Vol. 11, No. 3, 597, 2023.

Research output: Contribution to journal › Article › peer-review

Harvard

Bashkirtseva, IA, Pisarchik, AN & Ryashko, LB 2023, 'Coexisting Attractors and Multistate Noise-Induced Intermittency in a Cycle Ring of Rulkov Neurons', Mathematics, vol. 11, no. 3, 597. https://doi.org/10.3390/math11030597

APA

Bashkirtseva, I. A., Pisarchik, A. N., & Ryashko, L. B. (2023). Coexisting Attractors and Multistate Noise-Induced Intermittency in a Cycle Ring of Rulkov Neurons. Mathematics, 11(3), [597]. https://doi.org/10.3390/math11030597

Vancouver

Bashkirtseva IA, Pisarchik AN, Ryashko LB. Coexisting Attractors and Multistate Noise-Induced Intermittency in a Cycle Ring of Rulkov Neurons. Mathematics. 2023;11(3):597. doi: 10.3390/math11030597

Author

Bashkirtseva, Irina A. ; Pisarchik, Alexander N. ; Ryashko, Lev B. / Coexisting Attractors and Multistate Noise-Induced Intermittency in a Cycle Ring of Rulkov Neurons. In: Mathematics. 2023 ; Vol. 11, No. 3.

BibTeX

@article{b703703c05b44730b6ac881f41e7f9ea,
title = "Coexisting Attractors and Multistate Noise-Induced Intermittency in a Cycle Ring of Rulkov Neurons",
abstract = "We study dynamics of a unidirectional ring of three Rulkov neurons coupled by chemical synapses. We consider both deterministic and stochastic models. In the deterministic case, the neural dynamics transforms from a stable equilibrium into complex oscillatory regimes (periodic or chaotic) when the coupling strength is increased. The coexistence of complete synchronization, phase synchronization, and partial synchronization is observed. In the partial synchronization state either two neurons are synchronized and the third is in antiphase, or more complex combinations of synchronous and asynchronous interaction occur. In the stochastic model, we observe noise-induced destruction of complete synchronization leading to multistate intermittency between synchronous and asynchronous modes. We show that even small noise can transform the system from the regime of regular complete synchronization into the regime of asynchronous chaotic oscillations.",
author = "Bashkirtseva, {Irina A.} and Pisarchik, {Alexander N.} and Ryashko, {Lev B.}",
note = "The work was supported by the Russian Science Foundation (N 21-11-00062).",
year = "2023",
doi = "10.3390/math11030597",
language = "English",
volume = "11",
journal = "Mathematics",
issn = "2227-7390",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "3",

}

RIS

TY - JOUR

T1 - Coexisting Attractors and Multistate Noise-Induced Intermittency in a Cycle Ring of Rulkov Neurons

AU - Bashkirtseva, Irina A.

AU - Pisarchik, Alexander N.

AU - Ryashko, Lev B.

N1 - The work was supported by the Russian Science Foundation (N 21-11-00062).

PY - 2023

Y1 - 2023

N2 - We study dynamics of a unidirectional ring of three Rulkov neurons coupled by chemical synapses. We consider both deterministic and stochastic models. In the deterministic case, the neural dynamics transforms from a stable equilibrium into complex oscillatory regimes (periodic or chaotic) when the coupling strength is increased. The coexistence of complete synchronization, phase synchronization, and partial synchronization is observed. In the partial synchronization state either two neurons are synchronized and the third is in antiphase, or more complex combinations of synchronous and asynchronous interaction occur. In the stochastic model, we observe noise-induced destruction of complete synchronization leading to multistate intermittency between synchronous and asynchronous modes. We show that even small noise can transform the system from the regime of regular complete synchronization into the regime of asynchronous chaotic oscillations.

AB - We study dynamics of a unidirectional ring of three Rulkov neurons coupled by chemical synapses. We consider both deterministic and stochastic models. In the deterministic case, the neural dynamics transforms from a stable equilibrium into complex oscillatory regimes (periodic or chaotic) when the coupling strength is increased. The coexistence of complete synchronization, phase synchronization, and partial synchronization is observed. In the partial synchronization state either two neurons are synchronized and the third is in antiphase, or more complex combinations of synchronous and asynchronous interaction occur. In the stochastic model, we observe noise-induced destruction of complete synchronization leading to multistate intermittency between synchronous and asynchronous modes. We show that even small noise can transform the system from the regime of regular complete synchronization into the regime of asynchronous chaotic oscillations.

UR - https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=tsmetrics&SrcApp=tsm_test&DestApp=WOS_CPL&DestLinkType=FullRecord&KeyUT=000930061800001

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85158843917

U2 - 10.3390/math11030597

DO - 10.3390/math11030597

M3 - Article

VL - 11

JO - Mathematics

JF - Mathematics

SN - 2227-7390

IS - 3

M1 - 597

ER -

ID: 35452935