IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v95y2022i4d10.1140_epjb_s10051-022-00324-x.html
   My bibliography  Save this article

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

Author

Listed:
  • Jules Tagne Fossi

    (University of Yaoundé I
    Centre d’Excellence Africain des Technologies de l’Information et de la Communication (CETIC) Université de Yaoundé I)

  • Vandi Deli

    (University of Douala)

  • Hélène Carole Edima

    (University of Ngaoundéré)

  • Zeric Tabekoueng Njitacke

    (University of Buea
    Lodz University of Technology)

  • Florent Feudjio Kemwoue

    (University of Yaoundé I
    Centre d’Excellence Africain des Technologies de l’Information et de la Communication (CETIC) Université de Yaoundé I)

  • Jacques Atangana

    (University of Yaoundé I)

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. Graphical abstract

Suggested Citation

  • Jules Tagne Fossi & Vandi Deli & Hélène Carole Edima & Zeric Tabekoueng Njitacke & Florent Feudjio Kemwoue & Jacques Atangana, 2022. "Phase synchronization between two thermo-photoelectric neurons coupled through a Josephson Junction," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(4), pages 1-17, April.
    • Handle: RePEc:spr:eurphb:v:95:y:2022:i:4:d:10.1140_epjb_s10051-022-00324-x
    DOI: 10.1140/epjb/s10051-022-00324-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1140/epjb/s10051-022-00324-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1140/epjb/s10051-022-00324-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mostaghimi, Soudeh & Nazarimehr, Fahimeh & Jafari, Sajad & Ma, Jun, 2019. "Chemical and electrical synapse-modulated dynamical properties of coupled neurons under magnetic flow," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 42-56.
    2. Liu, Zhilong & Ma, Jun & Zhang, Ge & Zhang, Yin, 2019. "Synchronization control between two Chua′s circuits via capacitive coupling," Applied Mathematics and Computation, Elsevier, vol. 360(C), pages 94-106.
    3. Xu, Ying & Guo, Yeye & Ren, Guodong & Ma, Jun, 2020. "Dynamics and stochastic resonance in a thermosensitive neuron," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    4. Ge, Mengyan & Jia, Ya & Xu, Ying & Lu, Lulu & Wang, Huiwen & Zhao, Yunjie, 2019. "Wave propagation and synchronization induced by chemical autapse in chain Hindmarsh–Rose neural network," Applied Mathematics and Computation, Elsevier, vol. 352(C), pages 136-145.
    5. Zhou, Ping & Yao, Zhao & Ma, Jun & Zhu, Zhigang, 2021. "A piezoelectric sensing neuron and resonance synchronization between auditory neurons under stimulus," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    6. Fabrizio Gabbiani & Holger G. Krapp & Christof Koch & Gilles Laurent, 2002. "Multiplicative computation in a visual neuron sensitive to looming," Nature, Nature, vol. 420(6913), pages 320-324, November.
    7. Njitacke, Zeric Tabekoueng & Doubla, Isaac Sami & Mabekou, Sandrine & Kengne, Jacques, 2020. "Hidden electrical activity of two neurons connected with an asymmetric electric coupling subject to electromagnetic induction: Coexistence of patterns and its analog implementation," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    8. Wang, Zhen & Parastesh, Fatemeh & Rajagopal, Karthikeyan & Hamarash, Ibrahim Ismael & Hussain, Iqtadar, 2020. "Delay-induced synchronization in two coupled chaotic memristive Hopfield neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fossi, Jules Tagne & Njitacke, Zeric Tabekoueng & Tankeu, William Nguimeya & Mendimi, Joseph Marie & Awrejcewicz, Jan & Atangana, Jacques, 2023. "Phase synchronization and coexisting attractors in a model of three different neurons coupled via hybrid synapses," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Fan & Liu, Shuai & Li, Xiaola, 2022. "Pattern selection in thermosensitive neuron network induced by noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    2. Fossi, Jules Tagne & Njitacke, Zeric Tabekoueng & Tankeu, William Nguimeya & Mendimi, Joseph Marie & Awrejcewicz, Jan & Atangana, Jacques, 2023. "Phase synchronization and coexisting attractors in a model of three different neurons coupled via hybrid synapses," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    3. Sun, Guoping & Yang, Feifei & Ren, Guodong & Wang, Chunni, 2023. "Energy encoding in a biophysical neuron and adaptive energy balance under field coupling," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    4. Shadizadeh, S. Mohadeseh & Nazarimehr, Fahimeh & Jafari, Sajad & Rajagopal, Karthikeyan, 2022. "Investigating different synaptic connections of the Chay neuron model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    5. Yao, Zhao & Wang, Chunni, 2021. "Control the collective behaviors in a functional neural network," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    6. Ma, Xiaowen & Xu, Ying, 2022. "Taming the hybrid synapse under energy balance between neurons," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    7. Yao, Zhao & Wang, Chunni, 2022. "Collective behaviors in a multiple functional network with hybrid synapses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    8. Njitacke, Zeric Tabekoueng & Ramadoss, Janarthanan & Takembo, Clovis Ntahkie & Rajagopal, Karthikeyan & Awrejcewicz, Jan, 2023. "An enhanced FitzHugh–Nagumo neuron circuit, microcontroller-based hardware implementation: Light illumination and magnetic field effects on information patterns," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    9. Njitacke, Zeric Tabekoueng & Ramakrishnan, Balamurali & Rajagopal, Karthikeyan & Fonzin Fozin, Théophile & Awrejcewicz, Jan, 2022. "Extremely rich dynamics of coupled heterogeneous neurons through a Josephson junction synapse," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    10. Zhou, Ping & Hu, Xikui & Zhu, Zhigang & Ma, Jun, 2021. "What is the most suitable Lyapunov function?," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    11. Wang, Guowei & Wu, Yong & Xiao, Fangli & Ye, Zhiqiu & Jia, Ya, 2022. "Non-Gaussian noise and autapse-induced inverse stochastic resonance in bistable Izhikevich neural system under electromagnetic induction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    12. Yu, Dong & Wu, Yong & Yang, Lijian & Zhao, Yunjie & Jia, Ya, 2023. "Effect of topology on delay-induced multiple resonances in locally driven systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    13. Xie, Ying & Zhou, Ping & Yao, Zhao & Ma, Jun, 2022. "Response mechanism in a functional neuron under multiple stimuli," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    14. Feifei Yang & Xikui Hu & Guodong Ren & Jun Ma, 2023. "Synchronization and patterns in a memristive network in noisy electric field," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(6), pages 1-14, June.
    15. Gao, Chenghua & Qiao, Shuai & An, Xinlei, 2022. "Global multistability and mechanisms of a memristive autapse-based Filippov Hindmash-Rose neuron model," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    16. Mondal, Arnab & Upadhyay, Ranjit Kumar & Mondal, Argha & Sharma, Sanjeev Kumar, 2022. "Emergence of Turing patterns and dynamic visualization in excitable neuron model," Applied Mathematics and Computation, Elsevier, vol. 423(C).
    17. Yu, Dong & Wang, Guowei & Ding, Qianming & Li, Tianyu & Jia, Ya, 2022. "Effects of bounded noise and time delay on signal transmission in excitable neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    18. Hu, Jingting & Bao, Han & Xu, Quan & Chen, Mo & Bao, Bocheng, 2024. "Synchronization generations and transitions in two map-based neurons coupled with locally active memristor," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    19. Xing, Miaomiao & Song, Xinlin & Wang, Hengtong & Yang, Zhuoqin & Chen, Yong, 2022. "Frequency synchronization and excitabilities of two coupled heterogeneous Morris-Lecar neurons," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    20. Lu, Lulu & Ge, Mengyan & Xu, Ying & Jia, Ya, 2019. "Phase synchronization and mode transition induced by multiple time delays and noises in coupled FitzHugh–Nagumo model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:eurphb:v:95:y:2022:i:4:d:10.1140_epjb_s10051-022-00324-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.