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ORIGINAL RESEARCH article
Front. Neurosci.
Sec. Neuromorphic Engineering
Volume 18 - 2024 |
doi: 10.3389/fnins.2024.1456386
This article is part of the Research Topic Novel Memristor-Based Devices and Circuits for Neuromorphic and AI Applications Volume II View all articles
Memristor-based model of neuronal excitability and synaptic potentiation
Provisionally accepted- 1 Laboratory of Stochastic Multistable Systems, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
- 2 Institute of Nanotechnologies Electronics and Equipment Engineering, Southern Federal University, Rostov-on-Don, Rostov Oblast, Russia
- 3 Department of Engineering, University of Messina, Messina, Sicilia, Italy
- 4 Institute for Artificial Intelligence Research and Development of Serbia, Novi Sad, Vojvodina, Serbia
- 5 ITIS, Kazan Federal University, Kazan, Tatarstan, Russia
We investigated memristor based implementation of neuronal ion channels in mathematical model and experimental circuit of synaptically coupled neuronal oscillators. We took a simple FitzHugh-Nagumo equation system describing neuronal excitability. Nonlinearities induced by the voltage gated ion channels were modeled using memristive devices. We obtained three basic neuronal excitability modes including the excitable mode corresponding to a single spike generation, self-oscillation stable limit cycle mode with periodic spike trains and bistability between a fixed point and a limit cycle. Spike-burst oscillation mode was also found for specific parameters. Modeling synaptic transmission, we simulated postsynaptic response on periodic pulse stimulation. We found that due to charge accumulation effect in the memristive device the electronic synapse imitated qualitatively real biological synapse with potentiation effect with increasing amplitude of the response on a spike sequence
Keywords: Memristor, device, Neuron, Fitzhugh-Nagumo generator, Ion Channels, synaptic potentiation
Received: 28 Jun 2024; Accepted: 25 Oct 2024.
Copyright: © 2024 Kipelkin, Gerasimova, Belov, Guseinov, Talanov, Mikhaylov and Kazantsev. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Ivan M. Kipelkin, Laboratory of Stochastic Multistable Systems, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
Max O. Talanov, Department of Engineering, University of Messina, Messina, 98122, Sicilia, Italy
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