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

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 Fit...

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Published inThe European physical journal. B, Condensed matter physics Vol. 95; no. 4
Main Authors Fossi, Jules Tagne, Deli, Vandi, Edima, Hélène Carole, Njitacke, Zeric Tabekoueng, Kemwoue, Florent Feudjio, Atangana, Jacques
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2022
Springer
Springer Nature B.V
Subjects
Analysis
Circuit design
Circuits
Complex Systems
Condensed Matter Physics
Coupling
Electronic circuits
Electronic components
Fluid- and Aerodynamics
Josephson junctions
Magnetic fields
Neural circuitry
Neurons
Parameters
Photoelectricity
Physics
Physics and Astronomy
Regular Article - Statistical and Nonlinear Physics
Solid State Physics
Synapses
Synchronism
Thermistors
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Summary: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. Graphical abstract
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ISSN:1434-6028
1434-6036
DOI:10.1140/epjb/s10051-022-00324-x