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Effect of Noise variance in spiral wave suppression for a multi-layered neuron model with flux coupling modelled using a memristor

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Abstract

Dynamics of multi-layered neuronal network are challenging and spiral wave suppression is vital particularly in biological systems such as cortical tissue in brain, heart muscles etc., In this study, one-, two- and three-layer neuronal network of an exponential flux memristor-based Morris-Lecar neuron model subjected to low-frequency electromagnetic field (MLELF) is considered and the influence of noise variance in spiral wave suppression is investigated. A Box- Muller type Gaussian noise is used as stimulation and the influence of noise variance on neuronal network is studied. The results exposed the multilayer neuronal network influenced much by a very low noise variance on spiral wave suppression while compared with the single-layer network. As increase in noise variance, the dynamics of the spiral wave changes significantly and ended with turbulence. The study highlighted the spiral waves can be potentially suppressed even the network is under higher frequency external electric field using noise variance.

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Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request. This manuscript has associated data in a data repository. [Authors’ comment: The authors confirm that the data supporting the findings of this study are available within the article.]

References

  1. Z. Hou, J. Ma, X. Zhan, L. Yang, Y. Jia, Chaos, Solitons & Fractals, vol. 142, (2021)

  2. S.A. Mengiste, A. Ad, K. Arvind, bioRxiv, p. 2021.02.19.431963, (2021)

  3. K. Rajagopal, S. panahi, M. Chen, S. Jafari, B. Bao, Fractals, (2021)

  4. K. Rajagopal, S. Jafari, I. Moroz, A. Karthikeyan, A. Srinivasan, Chaos 31(7), 073117 (2021)

    Article  ADS  Google Scholar 

  5. Karthikeyan Rajagopal, Sajad Jafari, Chunbiao Li, Anitha Karthikeyan, Prakash Duraisamy, Chaos, Solitons & Fractals 146, 110855 (2021)

    Article  Google Scholar 

  6. Iqtadar Hussain, Sajad Jafari, Dibakar Ghosh, Matjaž Perc, Nonlinear Dyn. 104, 2711–2721 (2021)

    Article  Google Scholar 

  7. T. Górski, D. Depannemaecker, A. Destexhe, Neural Comput. 33(1), 41–66 (2021)

    Article  MathSciNet  Google Scholar 

  8. A. Karthikeyan, I. Moroz, K. Rajagopal, P. Duraisamy, Chaos Solitons Fractals 150, 111144 (2021)

    Article  Google Scholar 

  9. M. Zhan, R. Kapral, Phys Rev E 73(2), 026224 (2006)

    Article  ADS  Google Scholar 

  10. E.M.C. Flavio, H. Fenton, H.M. Hastings, S.J. Evans, Chaos 12(3), 852–892 (2002)

    Article  ADS  Google Scholar 

  11. F. Varela, J.-P. Lachaux, E. Rodriguez, J. Martinerie, Nat Rev Neurosci 2, 229–239 (2001)

    Article  Google Scholar 

  12. F. P. Zhen Wang, K. Rajagopal, I. I. Hamarash, I. Hussain, Chaos, Solitons & Fractals, 134, (2020)

  13. M. Shafiei, S. Jafari, F. Parastesh, M. Ozer, T. Kapitaniak, Matjăz Perc, Communications in Nonlinear Science and Numerical Simulation, 84, (2020)

  14. F. Tan, L. Zhou, J. Lu, Y. Chu. Journal of the Franklin Institute 357(15), (2020)

  15. W Q Y Wang, H X, Zheng Y H, Sci China Tech Sci, 57, 872-878, (2014)

  16. Y. Wang, J. Ma, Y. Xu, F. Wu, Z. P., International Journal of Bifurcation and Chaos, 27(2), 1750030-1750042, (2017)

  17. Y.X.J. Wu , J. Ma, PLoS One, 12, (2017)

  18. C.W.F. Wu, W. Jin, J. Ma, Phys. A 469, 81–88 (2017)

    Article  MathSciNet  Google Scholar 

  19. S. L. Faisal AA, Wolpert DM, Nat Rev Neurosci, 2008, 292-303, (2008)

  20. Z.H. Hou, H.W. Xin, Phys. Rev. Lett. 89, 280601 (2002)

    Article  Google Scholar 

  21. Karthikeyan Rajagopal, Sajad Jafari, Chunbiao Li, Anitha Karthikeyan, P. Duraisamy, Chaos, Solitons and Fractals 146, 110855 (2021)

    Article  Google Scholar 

  22. E.J. Müller, B.R. Munn, J.M. Shine, Nat. Commun. 11, 6337 (2020)

    Article  ADS  Google Scholar 

  23. Wu. Yong, Bing Wang, Xiaoxiao Zhang, Hao Chen, Int. J. Modern Phys. B 33(29), 1950354 (2019)

    Article  Google Scholar 

  24. Jun Ma, Lv. Mi, Ping Zhou, Xu. Ying, Tasawar Hayat, Appl. Math. Comput. 307, 321–328 (2017)

    MathSciNet  Google Scholar 

  25. S.J. Schiff, X.Y. Huang, J.Y. Wu, Phys Rev Lett 98, (2007)

  26. S. Shima, Y. Kuramoto, Phys. Rev. E 69, 036213 (2004)

    Article  ADS  Google Scholar 

  27. T. W. C. Huang X Y, Yang Q C, et al., J Neurosci, 24, 9897-9902, (2004)

  28. Y. Kuramoto, S. Shima, Progr. Theor. Phys. Suppl 150, 115 (2003)

    Article  ADS  Google Scholar 

  29. A.G. Richard, Chaos 12(3), 941–951 (2002)

    Article  Google Scholar 

  30. B. Gil, S. Alvin, G. Leon, Phys. Rev. Lett. 88(5), 058101 (2002)

    Article  Google Scholar 

  31. H. Sakaguchi, T. Fujimoto, Phys. Rev. E - Stat. Nonlinear Soft. Matter. Phys. 67(62), 0672021–3 (2003)

    Google Scholar 

  32. J. Ma, L. Huang, J. Tang, H.-P. Ying, W.-Y. Jin, Commun. Nonlinear Sci. Numer. Simul. 17, 4281–4293 (2012)

    Article  MathSciNet  ADS  Google Scholar 

  33. K. Rajagopal, F. Parastesh, H. Azarnoush, B. Hatef, S. Jafari, V. Berec, Chaos: an interdisciplinary, Journal of Nonlinear Science 29(4)(2019)

  34. J.W. Yan-Qiu Che, W.-J. Si, Xiang-Yang. Fei, Chaos, Solitons & Fractals 39, 454–462 (2009)

    Article  ADS  Google Scholar 

  35. Y. Feng, A.J.M. Khalaf, F.E. Alsaadi, T. Hayat, Viet Thanh Pham, Eur. Phys. H. Special Topics 228, 2371–2379 (2019)

    Article  ADS  Google Scholar 

  36. W. Zhen, R. Zahra, J. Sajad, E.A. Fawaz, S. Mitja, P. Matjaž, Chaos, Solitons & Fractals 128, 229–233 (2019)

    Article  MathSciNet  Google Scholar 

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Funding

This work was partially funded by the Research grant of Centre for Nonlinear Systems, Chennai Institute of Technology with reference number CIT/CNS/2021/RP-017.

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Ramakrishnan, B., Karthikeyan, A., Srinivasan, A. et al. Effect of Noise variance in spiral wave suppression for a multi-layered neuron model with flux coupling modelled using a memristor. Eur. Phys. J. Spec. Top. 231, 2439–2443 (2022). https://doi.org/10.1140/epjs/s11734-022-00478-w

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  • DOI: https://doi.org/10.1140/epjs/s11734-022-00478-w

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