Firing multistability in a locally active memristive neuron model
- 1. Hunan University. College of Computer Science and Electronic Engineering (China)
- 2. University of Hertfordshire. School of Engineering and Computer Science (United Kingdom)
Description
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.
Additional details
Identifiers
Publishing Information
- Journal Title
- Nonlinear Dynamics
- Journal Volume
- 100
- Journal Issue
- 4
- Journal Page Range
- p. 3667-3683
- ISSN
- 0924-090X
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 55081622
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING; S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Descriptors DEI
- BRAIN; CHAOS THEORY; COMPUTERIZED SIMULATION; DYNAMICAL SYSTEMS; ENGINEERING; FUNCTIONS; HUMAN POPULATIONS; HYSTERESIS; LIMIT CYCLE; MODE CONTROL; NERVE CELLS; NUMERICAL ANALYSIS; PERIODICITY; STOCHASTIC PROCESSES; TIME-SERIES ANALYSIS; TRANSIENTS
- Descriptors DEC
- ANIMAL CELLS; ATTRACTORS; BODY; CENTRAL NERVOUS SYSTEM; CONTROL; MATHEMATICS; NERVOUS SYSTEM; ORGANS; POPULATIONS; SIMULATION; SOMATIC CELLS; STATISTICS; VARIATIONS
Optional Information
- Copyright
- Copyright (c) 2020 © Springer Nature B.V. 2020