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Conformable fractional-order derivative based adaptive FitzHugh-Nagumo neuron model  Cover

Conformable fractional-order derivative based adaptive FitzHugh-Nagumo neuron model

Open Access
|Aug 2023

Abstract

Various neuron models have been proposed and are extensively examined in the scientific literature. The FitzHugh-Nagumo neuron model is one of the most well-known and studied models. The FitzHugh-Nagumo model is not biologically consistent but operationally simple. A fractional-order derivative is described as a derivative with a non-integer order. Caputo, Grünwald-Letnikov, and Riemann-Liouville are some of the well-known fractional order derivatives. However, a simple fractional-order derivative called the conformable fractional-order derivative has been proposed in the literature and it is much simpler to use. In literature, there are already neuron models with fractional-order derivatives. In this study, a FitzHugh-Nagumo model circuit with a conformable fractional derivative capacitor and conformable fractional derivative inductor is proposed. The proposed circuit is modelled, and its simulation results are given. The simulation results reveal that the model circuit shows both slow and fast adaptation in firing frequency under sustained current stimulation.

DOI: https://doi.org/10.2478/jee-2023-0035 | Journal eISSN: 1339-309X | Journal ISSN: 1335-3632
Language: English
Page range: 282 - 292
Published on: Aug 29, 2023
Published by: Slovak University of Technology in Bratislava
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2023 Ertuğrul Karakulak, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.