IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v182y2024ics0960077924004168.html
   My bibliography  Save this article

Higher-order-interaction in multiplex neuronal network with electric and synaptic coupling

Author

Listed:
  • Singh, Arpit
  • Verma, Umesh Kumar
  • Mishra, Ajay
  • Yadav, Kiran
  • Sharma, Amit
  • Varshney, Vaibhav

Abstract

We explore the emergence of various dynamic states within neurons interconnected in a multiplex setting with higher-order coupling. Using the Hindmarsh–Rose model as a representation of multiplex network dynamics, we examine scenarios where the primary layer is interacting through higher-order synaptic coupling while the secondary layer exhibits higher-order electric coupling. We examine the behavior of neurons within each layer individually and identify various emerging activity patterns, including synchronization, amplitude and oscillation death. When combining both layer through feedback mechanisms, we notice that the phenomenon of oscillation death shifts from the first layer to the second as the intralayer coupling intensifies. Multiplexing can also induces oscillation death in both the layers even when first layer is uncoupled. We also show that increasing the strength of synaptic coupling results in revival of oscillation in both the layers.

Suggested Citation

  • Singh, Arpit & Verma, Umesh Kumar & Mishra, Ajay & Yadav, Kiran & Sharma, Amit & Varshney, Vaibhav, 2024. "Higher-order-interaction in multiplex neuronal network with electric and synaptic coupling," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    • Handle: RePEc:eee:chsofr:v:182:y:2024:i:c:s0960077924004168
    DOI: 10.1016/j.chaos.2024.114864
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077924004168
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2024.114864?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. Frank Schweitzer & Giorgio Fagiolo & Didier Sornette & Fernando Vega-Redondo & Douglas R. White, 2009. "Economic Networks: What Do We Know And What Do We Need To Know?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(04n05), pages 407-422.
    2. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    3. L. V. Gambuzza & F. Patti & L. Gallo & S. Lepri & M. Romance & R. Criado & M. Frasca & V. Latora & S. Boccaletti, 2021. "Stability of synchronization in simplicial complexes," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    4. Li, Zhaoqing & Deng, Zhenghong & Han, Zhen & Alfaro-Bittner, Karin & Barzel, Baruch & Boccaletti, Stefano, 2021. "Contagion in simplicial complexes," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    5. Jonathan M. Levine & Jordi Bascompte & Peter B. Adler & Stefano Allesina, 2017. "Beyond pairwise mechanisms of species coexistence in complex communities," Nature, Nature, vol. 546(7656), pages 56-64, June.
    6. Rybalova, E.V. & Zakharova, A. & Strelkova, G.I., 2021. "Interplay between solitary states and chimeras in multiplex neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    7. Schülen, Leonhard & Janzen, David A. & Medeiros, Everton S. & Zakharova, Anna, 2021. "Solitary states in multiplex neural networks: Onset and vulnerability," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    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. Luca Gallo & Lucas Lacasa & Vito Latora & Federico Battiston, 2024. "Higher-order correlations reveal complex memory in temporal hypergraphs," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    2. Christos Ellinas & Neil Allan & Anders Johansson, 2016. "Exploring Structural Patterns Across Evolved and Designed Systems: A Network Perspective," Systems Engineering, John Wiley & Sons, vol. 19(3), pages 179-192, May.
    3. Biswas, Dhrubajyoti & Gupta, Sayan, 2024. "Symmetry-breaking higher-order interactions in coupled phase oscillators," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    4. Ancona, Camilla & Della Rossa, Fabio & Lo Iudice, Francesco & De Lellis, Pietro, 2024. "Percolation-induced explosive synchronization in pinning control," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    5. Li, Shumei & Yang, Chun & Yao, Zhiwen, 2024. "Simplicial epidemic model with individual resource," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 647(C).
    6. Shang, Yilun, 2022. "Sombor index and degree-related properties of simplicial networks," Applied Mathematics and Computation, Elsevier, vol. 419(C).
    7. Emerson, Isaac Arnold & Amala, Arumugam, 2017. "Protein contact maps: A binary depiction of protein 3D structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 782-791.
    8. Faedo, Nicolás & García-Violini, Demián & Ringwood, John V., 2021. "Controlling synchronization in a complex network of nonlinear oscillators via feedback linearisation and H∞-control," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    9. Xiao‐Bing Hu & Hang Li & XiaoMei Guo & Pieter H. A. J. M. van Gelder & Peijun Shi, 2019. "Spatial Vulnerability of Network Systems under Spatially Local Hazards," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 162-179, January.
    10. Ruiz Vargas, E. & Mitchell, D.G.V. & Greening, S.G. & Wahl, L.M., 2014. "Topology of whole-brain functional MRI networks: Improving the truncated scale-free model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 151-158.
    11. Igor Belykh & Mateusz Bocian & Alan R. Champneys & Kevin Daley & Russell Jeter & John H. G. Macdonald & Allan McRobie, 2021. "Emergence of the London Millennium Bridge instability without synchronisation," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    12. Berahmand, Kamal & Bouyer, Asgarali & Samadi, Negin, 2018. "A new centrality measure based on the negative and positive effects of clustering coefficient for identifying influential spreaders in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 41-54.
    13. Zhang, Yun & Liu, Yongguo & Li, Jieting & Zhu, Jiajing & Yang, Changhong & Yang, Wen & Wen, Chuanbiao, 2020. "WOCDA: A whale optimization based community detection algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    14. Soh, Harold & Lim, Sonja & Zhang, Tianyou & Fu, Xiuju & Lee, Gary Kee Khoon & Hung, Terence Gih Guang & Di, Pan & Prakasam, Silvester & Wong, Limsoon, 2010. "Weighted complex network analysis of travel routes on the Singapore public transportation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5852-5863.
    15. Wang, Qingyun & Duan, Zhisheng & Chen, Guanrong & Feng, Zhaosheng, 2008. "Synchronization in a class of weighted complex networks with coupling delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5616-5622.
    16. Andreas Koulouris & Ioannis Katerelos & Theodore Tsekeris, 2013. "Multi-Equilibria Regulation Agent-Based Model of Opinion Dynamics in Social Networks," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 11(1), pages 51-70.
    17. De Montis, Andrea & Ganciu, Amedeo & Cabras, Matteo & Bardi, Antonietta & Mulas, Maurizio, 2019. "Comparative ecological network analysis: An application to Italy," Land Use Policy, Elsevier, vol. 81(C), pages 714-724.
    18. He, He & Yang, Bo & Hu, Xiaoming, 2016. "Exploring community structure in networks by consensus dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 342-353.
    19. T. Botmart & N. Yotha & P. Niamsup & W. Weera, 2017. "Hybrid Adaptive Pinning Control for Function Projective Synchronization of Delayed Neural Networks with Mixed Uncertain Couplings," Complexity, Hindawi, vol. 2017, pages 1-18, August.
    20. Sgrignoli, P. & Agliari, E. & Burioni, R. & Schianchi, A., 2015. "Instability and network effects in innovative markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 108(C), pages 260-271.

    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:182:y:2024:i:c:s0960077924004168. 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.