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Complete synchronization in coupled type-I neurons

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Abstract

For a system of type-I neurons bidirectionally coupled through a nonlinear feedback mechanism, we discuss the issue of noise-induced complete synchronization (CS). For the inputs to the neurons, we point out that the rate of change of instantaneous frequency with the instantaneous phase of the stochastic inputs to each neuron matches exactly with that for the other in the event of CS of their outputs. Our observation can be exploited in practical situations to produce completely synchronized outputs in artificial devices. For excitatory-excitatory synaptic coupling, a functional dependence for the synchronization error on coupling and noise strengths is obtained. Finally, we report a noise-induced CS between nonidentical neurons coupled bidirectionally through random nonzero couplings in an all-to-all way in a large neuronal ensemble.

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References

  1. L M Pecora and T L Carroll, Phys. Rev. Lett. 64, 821 (1990)

    Article  MathSciNet  ADS  Google Scholar 

  2. D Hansel and H Sompolinsky, Phys. Rev. Lett. 68, 718 (1992)

    Article  ADS  Google Scholar 

  3. W Wang, G Perez and H A Cerdeira, Phys. Rev. E47, 2893 (1993)

    ADS  Google Scholar 

  4. C van Vreeswijk, L F Abbott and G B Ermentrout, J. Comput. Neurosci. 1, 313 (1994)

    Article  Google Scholar 

  5. D Hansel, G Mato and C Meunier, Neural Comput. 7, 307 (1995)

    Article  Google Scholar 

  6. B Ermentrout, Neural Comput. 8, 979 (1996)

    Article  Google Scholar 

  7. C Börgers and N Kopell, Neural Comput. 15, 509 (2003)

    Article  MATH  Google Scholar 

  8. C Börgers and N Kopell, Neural Comput. 17, 557 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  9. E Izhikevich, IEEE Trans. Neural Networks 10, 499 (1999)

    Article  Google Scholar 

  10. F E-N Hassan, Y Zhang, H A Cerdeira and A F Ibiyinka, Chaos 13, 1216 (2003)

    Article  MATH  MathSciNet  ADS  Google Scholar 

  11. F E-N Hassan, M Paulsamy, F F Fernando and H A Cerdeira, Chaos 19, 013103 (2009)

    Article  Google Scholar 

  12. S Sinha, Phys. Rev. E66, 016209 (2002)

    ADS  Google Scholar 

  13. M P K Jampa, A R Sonawane, P M Gade and S Sinha, Phys. Rev. E75, 026215 (2007)

    MathSciNet  ADS  Google Scholar 

  14. A Pikovsky, M Rosenblum and J Kurths, Synchronization: A universal concept in nonlinear sciences (Cambridge University Press, Cambridge, 2001)

    MATH  Google Scholar 

  15. H C Tuckwell, Stochastic processes in neurosciences (SIAM, Philadelphia, 1989)

    Google Scholar 

  16. A L Hodgkin and A F Huxley, J. Physiol. (London) 117, 500 (1952)

    Google Scholar 

  17. J R Rinzel and G B Ermentrout, in: Methods of neuronal modeling edited by C Koch and I Segev (MIT Press, Cambridge, MA, USA, 1989) pp. 135–169

    Google Scholar 

  18. C Koch, Biophysics of computation: Information processing in single neurons (Oxford University Press, NY, 1999)

    Google Scholar 

  19. W Lim and S-Y Kim, J. Korean Phys. Soc. 50, 219 (2007)

    Article  Google Scholar 

  20. V S Anishchenko, V V Astakhov, A B Neiman, T E Vadisova and L Schimansky-Geier, Nonlinear dynamics of chaotic and stochastic systems (Springer-Verlag, Berlin, 2002)

    MATH  Google Scholar 

  21. C Zhou and J Kurths, Phys. Rev. Lett. 88, 230602 (2002)

    Article  ADS  Google Scholar 

  22. C Zhou and J Kurths, Chaos 13, 401 (2003)

    Article  ADS  Google Scholar 

  23. Y Wang, D T W Chik and Z D Wang, Phys. Rev. E61, 740 (2000)

    ADS  Google Scholar 

  24. R Toral, C R Mirasso, E Hernández-Garcia and O Piro, Chaos 11, 665 (2001)

    Article  MATH  ADS  Google Scholar 

  25. D He, P Shi and L Stone, Phys. Rev. E67, 027201 (2003)

    ADS  Google Scholar 

  26. T S Parker and L O Chua, Practical numerical algorithms for chaotic systems (Springer-Verlag, Berlin, 1998)

    Google Scholar 

  27. J P Eckmann and D Ruelle, Rev. Mod. Phys. 57, 617 (1985)

    Article  MathSciNet  ADS  Google Scholar 

  28. J Gao and Z Zheng, Phys. Rev. E49, 3807 (1994)

    ADS  Google Scholar 

  29. W Rümelin, SIAM J. Numer. Anal. 19, 604 (1982)

    Article  MATH  MathSciNet  Google Scholar 

  30. J Hansen and C Penland, Monthly Weather Rev. 134, 3006 (2006)

    Article  ADS  Google Scholar 

  31. P Kloeden and E Platen, Numerical solutions of stochastic differential equations (Springer-Verlag, Berlin, 1992)

    Google Scholar 

  32. P Hänggi and H Thomas, Phys. Rep. 88, 207 (1982)

    Article  MathSciNet  ADS  Google Scholar 

  33. N Malik, B Ashok and J Balakrishnan (submitted) (2009)

  34. W Singer and C Gray, Annu. Rev. Neurosci. 18, 555 (1995)

    Article  Google Scholar 

  35. A K Kreiter and W Singer, in: Brain theory: Biological basis and computational theory of vision edited by A Aertsen and V Braitenberg (Elsevier, Amsterdam, 1996)

    Google Scholar 

  36. W Gerstner, A F Kreiter, H Markram and A V M Herz, Proc. Natl. Acad. Sci. USA 94, 12740 (1997)

    Article  ADS  Google Scholar 

  37. W Singer, Neuron 24, 49 (1999)

    Article  Google Scholar 

  38. R Ritz and T J Sejnowski, Curr. Opin. Neurobiol. 7, 536 (1997)

    Article  Google Scholar 

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Correspondence to J. Balakrishnan.

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Malik, N., Ashok, B. & Balakrishnan, J. Complete synchronization in coupled type-I neurons. Pramana - J Phys 74, 189–205 (2010). https://doi.org/10.1007/s12043-010-0020-0

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  • DOI: https://doi.org/10.1007/s12043-010-0020-0

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