IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v176y2023ics0960077923010056.html
   My bibliography  Save this article

Transitions to synchronization induced by synaptic increasing in coupled tonic neurons with electrical synapses

Author

Listed:
  • Li, Rui
  • Xu, Bang-Lin
  • Chen, De-Bao
  • Zhou, Jian-Fang
  • Yuan, Wu-Jie

Abstract

Experimental evidence had suggested that the net synaptic strength of nervous system increases during wakefulness. By using a model of coupled tonic neurons, we studied transitions to synchronization induced by synaptic increasing. Our findings revealed that in the presence of electrical synapses, synaptic increasing initially leads to a transition from desynchronized tonic activity (DTA) to desynchronized bursting activity (DBA). This DBA then transitions towards bursting activity with burst synchronization (BABS), followed by bursting activity with spike synchronization (BASS). As the synaptic strength continues to increase, there is a transition from BASS to approximately synchronized tonic activity (ASTA) once the synaptic strength reaches a critical value. Finally, completely synchronized tonic activity (CSTA) emerges when the synaptic strength reaches another critical value. Notably, the values of these two critical synaptic strengths, for ASTA and CSTA respectively, depend solely on the absolute value of the second largest eigenvalue of network coupling matrix. Through numerical and analytical methods, we demonstrated that both of these critical values and the absolute value of the eigenvalue follow a power-law relationship with exponent −1. These results suggested that the transitions to synchronization driven by synaptic increasing are a multi-time-scale phenomenon consisting of six stages: DTA, DBA, BABS, BASS, ASTA, and CSTA. We also briefly discussed the meaningful implications of sleep deprivation and the further challenging investigations that arise from these findings.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:chsofr:v:176:y:2023:i:c:s0960077923010056
    DOI: 10.1016/j.chaos.2023.114104
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923010056
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.114104?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. Cui, Xueke & Li, Hong-Li & Zhang, Long & Hu, Cheng & Bao, Haibo, 2023. "Complete synchronization for discrete-time fractional-order coupled neural networks with time delays," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    2. Zhen Wang & Marko Jusup & Lei Shi & Joung-Hun Lee & Yoh Iwasa & Stefano Boccaletti, 2018. "Exploiting a cognitive bias promotes cooperation in social dilemma experiments," Nature Communications, Nature, vol. 9(1), pages 1-7, December.
    3. Parastesh, Fatemeh & Azarnoush, Hamed & Jafari, Sajad & Hatef, Boshra & Perc, Matjaž & Repnik, Robert, 2019. "Synchronizability of two neurons with switching in the coupling," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 217-223.
    4. Xu, Bang-Lin & Zhou, Jian-Fang & Li, Rui & Jiang, En-Hua & Yuan, Wu-Jie, 2023. "Neural dynamic transitions caused by changes of synaptic strength in heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    5. Zhou, Ping & Ma, Jun & Xu, Ying, 2023. "Phase synchronization between neurons under nonlinear coupling via hybrid synapse," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    6. Jia Wang & Zhiping Wang & Ping Yu & Peiwen Wang, 2022. "The SEIR Dynamic Evolutionary Model with Markov Chains in Hyper Networks," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    Full references (including those not matched with items on IDEAS)

    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. Yang, Xuenan & Peng, Yu & Xiao, Yue & Wu, Xue, 2019. "Nonlinear dynamics of a duopoly Stackelberg game with marginal costs," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 185-191.
    2. 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).
    3. Liu, Chen & Guo, Hao & Li, Zhibin & Gao, Xiaoyuan & Li, Shudong, 2019. "Coevolution of multi-game resolves social dilemma in network population," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 402-407.
    4. Wang, Qiuling & Du, Chunpeng, 2019. "Impact of expansion of priority range on cooperation in the prisoner's dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 129(C), pages 77-80.
    5. Yu, Xihong & Bao, Han & Chen, Mo & Bao, Bocheng, 2023. "Energy balance via memristor synapse in Morris-Lecar two-neuron network with FPGA implementation," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    6. Gao, Lei & Li, Yaotang & Wang, Zhen & Wang, Rui-Wu, 2022. "Asymmetric strategy setup solve the Prisoner’s Dilemma of the evolution of mutualism," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    7. 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).
    8. Dehghani, Sedigheh & Nazarimehr, Fahimeh & Jafari, Sajad, 2021. "How can cultural conditions affect society’s decisions?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    9. Wang, Xianjia & Yang, Zhipeng & Liu, Yanli & Chen, Guici, 2023. "A reinforcement learning-based strategy updating model for the cooperative evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    10. Cheng, Yuan & Xue, Yanbo & Chang, Meng, 2020. "Career choice as an extended spatial evolutionary public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    11. Iwamura, Yoshiro & Nagashima, Keisuke & Tanimoto, Jun, 2020. "Evolutionary dynamics of a 3-strategy game: Cooperator, defector and costly cooperative loner strategic types," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    12. Sun, Peng & Zhang, Jun, 2020. "Group decision under uncertain information," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    13. Yang, Han-Xin & Yang, Jing, 2019. "Reputation-based investment strategy promotes cooperation in public goods games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 886-893.
    14. Kafraj, Mohadeseh Shafiei & Parastesh, Fatemeh & Jafari, Sajad, 2020. "Firing patterns of an improved Izhikevich neuron model under the effect of electromagnetic induction and noise," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    15. Wu, Yu’e & Zhang, Zhipeng & Wang, Xinyu & Yan, Ming & Zhang, Qingfeng & Zhang, Shuhua, 2021. "Evolution of cooperation in the multigame on a two-layer square network," Applied Mathematics and Computation, Elsevier, vol. 400(C).
    16. Feng, Meiling & Li, Xuezhu & Zhao, Dawei & Xia, Chengyi, 2023. "Evolutionary dynamics with the second-order reputation in the networked N-player trust game," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
    17. Guan, Junbiao & Wang, Kaihua, 2020. "Cooperative evolution in pedestrian room evacuation considering different individual behaviors," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    18. Lv, Ran & Qian, Jia-Li & Hao, Qing-Yi & Wu, Chao-Yun & Guo, Ning & Ling, Xiang, 2024. "The impact of reputation-based heterogeneous evaluation and learning on cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    19. Pu, Jia & Jia, Tao & Li, Ya, 2019. "Effects of time cost on the evolution of cooperation in snowdrift game," Chaos, Solitons & Fractals, Elsevier, vol. 125(C), pages 146-151.
    20. Sun, Wenjing & Tang, Ze & Feng, Jianwen & Park, Ju H., 2024. "Quasi-synchronization of heterogeneous neural networks with hybrid time delays via sampled-data saturating impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 182(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:176:y:2023:i:c:s0960077923010056. 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.