IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v169y2023ics096007792300139x.html
   My bibliography  Save this article

Phase synchronization between neurons under nonlinear coupling via hybrid synapse

Author

Listed:
  • Zhou, Ping
  • Ma, Jun
  • Xu, Ying

Abstract

Biological neurons and nonlinear circuits contain certain inner field energy, and an equivalent Hamilton energy function can be obtained to discern the dependence of firing modes on the energy flow. In this paper, a voltage-controlled resistor is used to connect two neural circuits, and hybrid synapse is activated to control the synchronization stability and mode transition in neurons under phase lock. Realistic stimuli can be combined signals within certain frequency band rather than simple periodic stimulus, and the firing patterns will show multiple modes by applying mixed signals. Similar coherence resonance is detected in an isolated neuron driven by the filtered signals. Therefore, chaotic signals are encoded to represent filtered waves with finite frequency band, and then the mixed signals are used to excite two neural circuits via nonlinear coupling. Hamilton energy for the coupled neurons via hybrid synapse is estimated to detect the controllability of synchronization between neurons. The nonlinear resistor along the coupling channel can reproduce the biophysical property of hybrid synapse accompanying with field coupling, which mainly contributes the energy exchange between neurons. It is confirmed that this hybrid synapse is effective to control the synchronization stability and phase lock even the neurons presenting with different firing patterns/modes. The results confirmed that nonlinear coupling via specific components is helpful to design hybrid synapse, and it is effective to block the bursting synchronization between neurons driven by filtered chaotic signals. Therefore, activation of this hybrid synapse can prevent the occurrence of seizure in nervous system.

Suggested Citation

  • Zhou, Ping & Ma, Jun & Xu, Ying, 2023. "Phase synchronization between neurons under nonlinear coupling via hybrid synapse," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    • Handle: RePEc:eee:chsofr:v:169:y:2023:i:c:s096007792300139x
    DOI: 10.1016/j.chaos.2023.113238
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096007792300139X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.113238?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. Zhou, Ping & Hu, Xikui & Zhu, Zhigang & Ma, Jun, 2021. "What is the most suitable Lyapunov function?," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    2. Hu, Wancheng & Zhang, Yibin & Ma, Rencai & Dai, Qionglin & Yang, Junzhong, 2022. "Synchronization between two linearly coupled reservoir computers," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    3. Sharma, Sanjeev Kumar & Mondal, Arnab & Mondal, Argha & Aziz-Alaoui, M.A. & Upadhyay, Ranjit Kumar & Ma, Jun, 2022. "Emergence of Canard induced mixed mode oscillations in a slow–fast dynamics of a biophysical excitable model," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    4. Lu, Jianquan & Guo, Xing & Huang, Tingwen & Wang, Zhen, 2019. "Consensus of signed networked multi-agent systems with nonlinear coupling and communication delays," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 153-162.
    5. Njitacke, Zeric Tabekoueng & Takembo, Clovis Ntahkie & Awrejcewicz, Jan & Fouda, Henri Paul Ekobena & Kengne, Jacques, 2022. "Hamilton energy, complex dynamical analysis and information patterns of a new memristive FitzHugh-Nagumo neural network," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    6. Yao, Zhao & Zhou, Ping & Alsaedi, Ahmed & Ma, Jun, 2020. "Energy flow-guided synchronization between chaotic circuits," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    7. 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.
    8. Rajagopal, Karthikeyan & Jafari, Sajad & Li, Chunbiao & Karthikeyan, Anitha & Duraisamy, Prakash, 2021. "Suppressing spiral waves in a lattice array of coupled neurons using delayed asymmetric synapse coupling," Chaos, Solitons & Fractals, Elsevier, vol. 146(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. Li, Rui & Xu, Bang-Lin & Chen, De-Bao & Zhou, Jian-Fang & Yuan, Wu-Jie, 2023. "Transitions to synchronization induced by synaptic increasing in coupled tonic neurons with electrical synapses," Chaos, Solitons & Fractals, Elsevier, vol. 176(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. 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).
    2. Wang, Chunni & Liu, Zhilong & Hobiny, Aatef & Xu, Wenkang & Ma, Jun, 2020. "Capturing and shunting energy in chaotic Chua circuit," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    3. Xu, Quan & Wang, Yiteng & Chen, Bei & Li, Ze & Wang, Ning, 2023. "Firing pattern in a memristive Hodgkin–Huxley circuit: Numerical simulation and analog circuit validation," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    4. Guo, Yeye & Wang, Chunni & Yao, Zhao & Xu, Ying, 2022. "Desynchronization of thermosensitive neurons by using energy pumping," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 602(C).
    5. Ma, Rencai & Dai, Qionglin & Li, Haihong & Yang, Junzhong, 2023. "Dynamics reconstruction in the presence of bistability by using reservoir computer," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    6. Tu, Zhengwen & Yang, Xinsong & Wang, Liangwei & Ding, Nan, 2019. "Stability and stabilization of quaternion-valued neural networks with uncertain time-delayed impulses: Direct quaternion method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    7. Ma, Zheng & Song, Jiasheng & Zhou, Jianping, 2022. "Reliable event-based dissipative filter design for discrete-time system with dynamic quantization and sensor fault," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    8. Lei, Yong & Xu, Xin-Jian & Wang, Xiaofan & Zou, Yong & Kurths, Jürgen, 2023. "A new criterion for optimizing synchrony of coupled oscillators," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    9. Wang, Zhenhua, 2022. "Consensus of continuous-time agent dynamics with unknown input and communication delays," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    10. 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).
    11. Kaviarasan, Boomipalagan & Kwon, Oh-Min & Park, Myeong Jin & Sakthivel, Rathinasamy, 2021. "Stochastic faulty estimator-based non-fragile tracking controller for multi-agent systems with communication delay," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    12. Hou, Yi-You & Lin, Ming-Hung & Saberi-Nik, Hassan & Arya, Yogendra, 2024. "Boundary analysis and energy feedback control of fractional-order extended Malkus–Robbins dynamo system," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
    13. Ma, Jun, 2024. "Energy function for some maps and nonlinear oscillators," Applied Mathematics and Computation, Elsevier, vol. 463(C).
    14. Zhou, Ping & Hu, Xikui & Zhu, Zhigang & Ma, Jun, 2021. "What is the most suitable Lyapunov function?," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    15. Yuemin Zheng & Jin Tao & Qinglin Sun & Hao Sun & Zengqiang Chen & Mingwei Sun, 2023. "Adaptive Active Disturbance Rejection Load Frequency Control for Power System with Renewable Energies Using the Lyapunov Reward-Based Twin Delayed Deep Deterministic Policy Gradient Algorithm," Sustainability, MDPI, vol. 15(19), pages 1-25, October.
    16. Ijaz Ahmed & Um-E-Habiba Alvi & Abdul Basit & Tayyaba Khursheed & Alwena Alvi & Keum-Shik Hong & Muhammad Rehan, 2022. "A novel hybrid soft computing optimization framework for dynamic economic dispatch problem of complex non-convex contiguous constrained machines," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-32, January.
    17. 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).
    18. Liu, Zhilong & Zhou, Ping & Ma, Jun & Hobiny, Aatef & Alzahrani, Faris, 2020. "Autonomic learning via saturation gain method, and synchronization between neurons," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    19. Ren, Lei & Lin, Ming-Hung & Abdulwahab, Abdulkareem & Ma, Jun & Saberi-Nik, Hassan, 2023. "Global dynamical analysis of the integer and fractional 4D hyperchaotic Rabinovich system," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    20. Weng, Tongfeng & Chen, Xiaolu & Ren, Zhuoming & Yang, Huijie & Zhang, Jie & Small, Michael, 2023. "Synchronization of multiple mobile reservoir computing oscillators in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).

    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:eee:chsofr:v:169:y:2023:i:c:s096007792300139x. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.