Eur. Phys. J. B (2022) 95: 66
https://doi.org/10.1140/epjb/s10051-022-00324-x

Regular Article - Statistical and Nonlinear Physics

Phase synchronization between two thermo-photoelectric neurons coupled through a Josephson Junction

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 Department of Pharmaceutical Sciences, Faculty of Medicine and Pharmaceutical Sciences, University of Douala, Douala, Cameroon
³ National School of Agro-Industrial Sciences, Food Microbiology and Biotechnology Laboratory, University of Ngaoundéré, Ngaoundéré, Cameroon
⁴ Department of Electrical and Electronic Engineering, College of Technology (COT), University of Buea, P.O.Box 63, Buea, 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 Yaoundé I, Yaoundé, Cameroon
⁷ Department of Automation, Biomechanics and Mechatronics, Lodz University of Technology, Lodz, Poland

^a jules_fossi@yahoo.fr
^f atanganajaques@yahoo.fr

Received: 6 December 2021
Accepted: 21 March 2022
Published online: 10 April 2022

Abstract

The transmission and encoding of information in the brain has been the subject of much research. The aim is to improve biophysical functions and to design reliable artificial synapses for the connection of several biological neurons. In this manuscript, it is coupled through a hybrid synapse two FitzHugh–Nagumo neural circuits driven simultaneously by a phototube and a thermistor. The hybrid synapse is based on an ideal Josephson Junction in parallel with a linear resistance. This configuration allows the evaluation of the external magnetic field in the neural circuit. Using the standard scale transformation on the physical variables and parameters, we obtain the mathematical model of the coupled neurons. A bifurcation analysis on the intrinsic parameters of the coupling channel is carried out to demonstrate the complete synchronization and phase synchronization. It can be seen a synchronization stability when the parameters of the coupling channel are well defined. To practically confirm these results, an electronic circuit is designed using discrete electronic components and multipliers. Thanks to the simulations in the PSpice software, we see that this circuit can well and well be used to estimate the effect of the external magnetic field on a coupled neural circuit and predict a stable synchronization.