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State transitions in the Morris-Lecar model under stable Lévy noise

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Abstract

This work is about the state transition of the stochastic Morris-Lecar neuronal model driven by symmetric α-stable Lévy noise. The considered system is bistable: a stable equilibrium (resting state) and a stable limit cycle (oscillating state), and there is an unstable limit cycle (borderline state) between them. Small disturbances may cause a transition between the two stable states, thus a deterministic quantity, namely the maximal likely trajectory, is used to analyze the transition phenomena in a non-Gaussian stochastic environment. According to the numerical experiment, we find that smaller jumps of the Lévy motion and smaller noise intensities can promote such transition from the sustained oscillating state to the resting state. It also can be seen that larger jumps of the Lévy motion and higher noise intensities are conducive for the transition from the borderline state to the sustained oscillating state. As a comparison, Brownian motion is also taken into account. The results show that whether it is the oscillating state or the borderline state, the system disturbed by Brownian motion will be transferred to the resting state under the selected noise intensity with a high probability.

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References

  1. H.C. Tuckwell,Introduction to theoretical neurobiology (Cambridge: Cambridge University Press), 1988

  2. E.M. Izhikevich,Dynamical Systems in Neuroscience (Cambridge: MIT press), 2007

  3. M.D. McDonnell, S. Ikeda, J.H. Manton, Biol. Cybern. 105, 55 (2011)

    Article  Google Scholar 

  4. T. Trappenberg,Fundamentals of computational neuroscience (Oxford, OUP Oxford, 2009)

  5. W.W. Lytton,From computer to brain: foundations of computational neuroscience (Springer Science & Business Media, Berlin, 2007)

  6. P. Dayan, L.F. Abbott,Theoretical neuroscience (MIT Press, Cambridge, 2001)

  7. N. Chakravarthy, K. Tsakalis, S. Sabesan, L. Iasemidis, Ann. Biomed. Eng. 37, 565 (2009)

    Article  Google Scholar 

  8. E.T. Rolls, G. Deco,The noisy brain: stochastic dynamics as a principle of brain function (Oxford University Press, Oxford, 2010)

  9. B.G. Ermentrout, D.H Terman,Mathematical Foundations of Neuroscience (Springer Science & Business Media, Berlin, 2010)

  10. I. Franović, K. Todorović, M. Perc, N. Vasović, N. Burić, Phys. Rev. E 92, 062911 (2015)

    Article  ADS  Google Scholar 

  11. I. Franović, M. Perc, K. Todorović, S. Kostić, N. Burić, Phys. Rev. E 92, 062912 (2015)

    Article  ADS  MathSciNet  Google Scholar 

  12. Y. Wang, J. Ma, Y. Xu, F. Wu, P. Zhou, Int. J. Bifurc. Chaos 27, 1750030 (2017)

    Article  Google Scholar 

  13. A. Longtin, Scholarpedia 8, 1618 (2013)

    Article  ADS  Google Scholar 

  14. B. Lindner, J. Garcıa-Ojalvo, A. Neiman, L. Schimansky-Geier, Phys. Rep. 392, 321 (2004)

    Article  ADS  Google Scholar 

  15. A. Patel, B. Kosko, IEEE Trans. Neural Networks 19, 1993 (2008)

    Article  Google Scholar 

  16. A. Patel, B. Kosko, Lévy noise benefits in neural signal detection, inIEEE International Conference on Acoustics, Speech and Signal Processing, 2007, Vol. 3, pp. III–1413

    Google Scholar 

  17. J.A. Roberts, T.W. Boonstra, M. Breakspear, Curr. Opin. Neurobiol. 31, 164 (2015)

    Article  Google Scholar 

  18. Y. Xu, J. Li, J. Feng, H. Zhang, W. Xu, J. Duan, Eur. Phys. J. B 86, 198 (2013)

    Article  ADS  Google Scholar 

  19. X. Sun, Q. Lu, Chin. Phys. Lett. 31, 020502 (2014)

    Article  ADS  Google Scholar 

  20. K. Ýr Jónsdóttir, A. Rønn-Nielsen, K. Mouridsen, E.B. Vedel Jensen, Scand. J. Stat. 40, 511 (2013)

    Article  MathSciNet  Google Scholar 

  21. M. Vinaya, R.P. Ignatius, Nonlinear Dyn. 94, 1133 (2018)

    Article  Google Scholar 

  22. Z. Wang, Y. Xu, H. Yang, Sci. China Technol. Sci. 59, 371 (2016)

    ADS  Google Scholar 

  23. J. Wu, Y. Xu, J. Ma, PLoS One 12, e0174330 (2017)

    Article  Google Scholar 

  24. B. Dybiec, E. Gudowska-Nowak, J. Stat. Mech. 2009, P05004 (2009)

    Google Scholar 

  25. Y. Li, Y. Xu, J. Kurths, Phys. Rev. E 96, 052121 (2017)

    Article  Google Scholar 

  26. Y. Li, Y. Xu, J. Kurths, X. Yue, Phys. Rev. E 94, 042222 (2016)

    Article  ADS  Google Scholar 

  27. Y. Xu, J. Feng, J.J. Li, H. Zhang, Chaos 23, 013110 (2013)

    Article  ADS  MathSciNet  Google Scholar 

  28. Y. Xu, J. Feng, J.J. Li, H. Zhang, Physica A 392, 4739 (2013)

    Article  ADS  MathSciNet  Google Scholar 

  29. Y. Xu, Y. Li, J. Li, J. Feng, H. Zhang, J. Stat. Phys. 158, 120 (2015)

    Article  ADS  MathSciNet  Google Scholar 

  30. M. Perc, Phys. Rev. E 76, 066203 (2007)

    Article  ADS  Google Scholar 

  31. K. Ishimura, A. Schmid, T. Asai, M. Motomura, Nonlinear Theory Appl. IEICE 7, 164 (2016)

    Article  ADS  Google Scholar 

  32. S.F. Duki, M.A. Taye, J. Stat. Phys. 171, 878 (2018)

    Article  ADS  MathSciNet  Google Scholar 

  33. I. Bashkirtseva, L. Ryashko, P. Stikhin, Int. J. Bifurc. Chaos 23, 1350092 (2013)

    Article  Google Scholar 

  34. M. Frey, E. Simiu, Physica D 63, 321 (1993)

    Article  ADS  MathSciNet  Google Scholar 

  35. I. Bashkirtseva, S. Fedotov, L. Ryashko, E. Slepukhina, Int. J. Bifurc. Chaos 26, 1630032 (2016)

    Article  Google Scholar 

  36. Y. Zheng, L. Serdukova, J. Duan, J. Kurths, Sci. Rep. 6 (2016)

  37. F. Wu, X. Chen, Y. Zheng, J. Duan, X. Li, Chaos 28, 075510 (2018)

    Article  ADS  MathSciNet  Google Scholar 

  38. S. Lim, J. Rinzel, J. Comput. Neurosci. 28, 1 (2010)

    Article  MathSciNet  Google Scholar 

  39. S. Tanabe, K. Pakdaman, Biol. Cybern. 85, 269 (2001)

    Article  Google Scholar 

  40. J. Touboul, Physica D 241, 1223 (2012)

    Article  ADS  MathSciNet  Google Scholar 

  41. C. Morris, H. Lecar, Biophys. J. 35, 193 (1981)

    Article  ADS  Google Scholar 

  42. D. Terman, J. Nonlinear Sci. 2, 135 (1992)

    Article  ADS  MathSciNet  Google Scholar 

  43. J.M. Newby, P.C. Bressloff, J.P. Keener, Phys. Rev. Lett. 111, 128101 (2013)

    Article  ADS  Google Scholar 

  44. T. Tateno, K. Pakdaman, Chaos 14, 511 (2004)

    Article  ADS  MathSciNet  Google Scholar 

  45. J.P. Keener, J.M. Newby, Phys. Rev. E 84, 011918 (2011)

    Article  ADS  Google Scholar 

  46. Y. Liu, R. Cai, J. Duan, Physica A 531, 121785 (2019)

    Article  MathSciNet  Google Scholar 

  47. C. Liu, X. Liu, S. Liu, Biol. Cybern. 108, 75 (2014)

    Article  Google Scholar 

  48. K. Tsumoto, H. Kitajima, T. Yoshinaga, K. Aihara, H. Kawakami, Neurocomputing 69, 293 (2006)

    Article  Google Scholar 

  49. O. Zeitouni, A. Dembo, Stochastics 20, 221 (1987)

    Article  MathSciNet  Google Scholar 

  50. K. Sato,Lévy Processes and Infinitely Divisible Distributions (Cambridge University Press, Cambridge, 1999)

  51. J. Bertoin,Lévy Processes (Cambridge University Press, Cambridge, 1998)

  52. D. Applebaum,Lévy Processes and Stochastic Calculus (Cambridge University Press, Cambridge, 2009)

  53. J. Duan,An Introduction to Stochastic Dynamics (Cambridge University Press, Cabridge, 2015)

  54. H. Wang, X. Chen, J. Duan, Int. J. Bifurc. Chaos 28, 1850017 (2018)

    Article  Google Scholar 

  55. X. Chen, F. Wu, J. Duan, J. Kurths, X. Li, Appl. Math. Comput. 348, 425 (2019)

    Article  MathSciNet  Google Scholar 

  56. T. Gao, J. Duan, X. Li, Appl. Math. Comput. 278, 1 (2016)

    Article  MathSciNet  Google Scholar 

  57. J. Wei, R. Tian, J. Math. Phys. 56, 031502 (2015)

    Article  ADS  MathSciNet  Google Scholar 

  58. X. Yang, J. Cao, Appl. Math. Modell. 34, 3631 (2010)

    Article  Google Scholar 

  59. M. Perc, M. Gosak, New J. Phys. 10, 053008 (2008)

    Article  ADS  Google Scholar 

  60. M. Gosak, D. Korošak, M. Marhl, New J. Phys. 13, 013012 (2011)

    Article  ADS  Google Scholar 

  61. Q. Zhu, J. Cao, R. Rakkiyappan, Nonlinear Dyn. 79, 1085 (2015)

    Article  Google Scholar 

Download references

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Correspondence to Yancai Liu.

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Cai, R., Liu, Y., Duan, J. et al. State transitions in the Morris-Lecar model under stable Lévy noise. Eur. Phys. J. B 93, 38 (2020). https://doi.org/10.1140/epjb/e2020-100422-2

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