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Firing multistability in a locally active memristive neuron model

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Firing multistability in a locally active memristive neuron model. / Lin, Hairong ; Wang, Chunhua; Sun, Yichuang; Yao, Wei.

In: Nonlinear Dynamics, Vol. 100, No. 4, 01.06.2020, p. 3667-3683.

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Lin, Hairong ; Wang, Chunhua ; Sun, Yichuang ; Yao, Wei. / Firing multistability in a locally active memristive neuron model. In: Nonlinear Dynamics. 2020 ; Vol. 100, No. 4. pp. 3667-3683.

Bibtex

@article{3a534b08af3442cb8a5664c76f21054f,
title = "Firing multistability in a locally active memristive neuron model",
abstract = "The theoretical, numerical and experimental demonstrations of firing dynamics in isolated neuron are of great significance for the understanding of neural function in human brain. In this paper, a new type of locally active and non-volatile memristor with three stable pinched hysteresis loops is presented. Then, a novel locally active memristive neuron model is established by using the locally active memristor as a connecting autapse, and both firing patterns and multistability in this neuronal system are investigated. We have confirmed that, on the one hand, the constructed neuron can generate multiple firing patterns like periodic bursting, periodic spiking, chaotic bursting, chaotic spiking, stochastic bursting, transient chaotic bursting and transient stochastic bursting. On the other hand, the phenomenon of firing multistability with coexisting four kinds of firing patterns can be observed via changing its initial states. It is worth noting that the proposed neuron exhibits such firing multistability previously unobserved in single neuron model. Finally, an electric neuron is designed and implemented, which is extremely useful for the practical scientific and engineering applications. The results captured from neuron hardware experiments match well with the theoretical and numerical simulation results.",
keywords = "Firing, Locally active memristor, Multistability, Neuron model, Neuronal circuit",
author = "Hairong Lin and Chunhua Wang and Yichuang Sun and Wei Yao",
note = "Funding Information: This work is supported by The Major Research Project of the National Natural Science Foundation of China (91964108), The National Natural Science Foundation of China (61971185), The Open Fund Project of Key Laboratory in Hunan Universities (18K010). Publisher Copyright: {\textcopyright} 2020, Springer Nature B.V. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2020",
month = jun,
day = "1",
doi = "10.1007/s11071-020-05687-3",
language = "English",
volume = "100",
pages = "3667--3683",
journal = "Nonlinear Dynamics",
issn = "0924-090X",
publisher = "Springer",
number = "4",

}

RIS

TY - JOUR

T1 - Firing multistability in a locally active memristive neuron model

AU - Lin, Hairong

AU - Wang, Chunhua

AU - Sun, Yichuang

AU - Yao, Wei

N1 - Funding Information: This work is supported by The Major Research Project of the National Natural Science Foundation of China (91964108), The National Natural Science Foundation of China (61971185), The Open Fund Project of Key Laboratory in Hunan Universities (18K010). Publisher Copyright: © 2020, Springer Nature B.V. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/6/1

Y1 - 2020/6/1

N2 - The theoretical, numerical and experimental demonstrations of firing dynamics in isolated neuron are of great significance for the understanding of neural function in human brain. In this paper, a new type of locally active and non-volatile memristor with three stable pinched hysteresis loops is presented. Then, a novel locally active memristive neuron model is established by using the locally active memristor as a connecting autapse, and both firing patterns and multistability in this neuronal system are investigated. We have confirmed that, on the one hand, the constructed neuron can generate multiple firing patterns like periodic bursting, periodic spiking, chaotic bursting, chaotic spiking, stochastic bursting, transient chaotic bursting and transient stochastic bursting. On the other hand, the phenomenon of firing multistability with coexisting four kinds of firing patterns can be observed via changing its initial states. It is worth noting that the proposed neuron exhibits such firing multistability previously unobserved in single neuron model. Finally, an electric neuron is designed and implemented, which is extremely useful for the practical scientific and engineering applications. The results captured from neuron hardware experiments match well with the theoretical and numerical simulation results.

AB - The theoretical, numerical and experimental demonstrations of firing dynamics in isolated neuron are of great significance for the understanding of neural function in human brain. In this paper, a new type of locally active and non-volatile memristor with three stable pinched hysteresis loops is presented. Then, a novel locally active memristive neuron model is established by using the locally active memristor as a connecting autapse, and both firing patterns and multistability in this neuronal system are investigated. We have confirmed that, on the one hand, the constructed neuron can generate multiple firing patterns like periodic bursting, periodic spiking, chaotic bursting, chaotic spiking, stochastic bursting, transient chaotic bursting and transient stochastic bursting. On the other hand, the phenomenon of firing multistability with coexisting four kinds of firing patterns can be observed via changing its initial states. It is worth noting that the proposed neuron exhibits such firing multistability previously unobserved in single neuron model. Finally, an electric neuron is designed and implemented, which is extremely useful for the practical scientific and engineering applications. The results captured from neuron hardware experiments match well with the theoretical and numerical simulation results.

KW - Firing

KW - Locally active memristor

KW - Multistability

KW - Neuron model

KW - Neuronal circuit

UR - http://www.scopus.com/inward/record.url?scp=85084859253&partnerID=8YFLogxK

U2 - 10.1007/s11071-020-05687-3

DO - 10.1007/s11071-020-05687-3

M3 - Article

VL - 100

SP - 3667

EP - 3683

JO - Nonlinear Dynamics

JF - Nonlinear Dynamics

SN - 0924-090X

IS - 4

ER -