Eur. Phys. J. Spec. Top. (2022) 231: 993-1004
https://doi.org/10.1140/epjs/s11734-021-00311-w

Regular Article

Bifurcations analysis and experimental study of the dynamics of a thermosensitive neuron conducted simultaneously by photocurrent and thermistance

¹ Laboratory of Energy-Electric and Electronic Systems, Department of Physics, Faculty of Science, University of Yaoundé I, P.O. Box 812, Yaoundé, Cameroon
² National School of Agro-Industrial Sciences, Food Microbiology and Biotechnology Laboratory, University of Ngaoundéré, Ngaoundéré, Cameroon
³ Department of Electrical and Electronic Engineering, College of Technology (COT), University of Buea, P.O. Box 63, Buea, Cameroon
⁴ Galenic Pharmacy and Pharmaceutical Legislation Laboratory, Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, Yaoundé, Cameroon
⁵ Department of Physics, Higher Teacher Training College Yaoundé, University of Yaoundé I, Yaoundé, Cameroon
⁶ Centre d’Excellence Africain des Technologies de l’Information et de la Communication (CETIC) Université de YaoundéI, Yaoundé, Cameroon

Received: 10 April 2021
Accepted: 25 October 2021
Published online: 22 November 2021

Abstract

The literature contains evidence that the membrane potential of a biological neuron exhibits several behaviors such as quiescent, spiking, bursting and chaotic states when the external excitation current is adjusted. This paper proposes a model of the photosensitive neuron and the thermosensitive one driven simultaneously, by optical signals and heat acting as the external exciter current. The analysis of the equilibrium points and the stability of the model is carried out. It is shown that the temperature variation produced by the thermistor modifies the number and the nature of the equilibrium points of the system. This temperature also induces a Hopf bifurcation showing that the neuron can go from a state of rest to an oscillatory state and vice versa. The excitation current produced by the phototube and the thermistor makes it possible to generate behaviors already observed in the literature (biological characteristics of the neuron) and complex phenomena. These complex phenomena are among others, bifurcations such as period-doubling, reverse period-doubling, intermittence (crisis) and antimonotonicity. Finally, an on-board system implementation of this neuron model is presented using microcontroller technology. It can be seen that these special behaviors can be easily produced in their actual electrical nature. This constitutes an important tool that can be applied in biomedical technology for the design of artificial neurons.