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Complex dynamics of a four neuron network model having a pair of short-cut connections with multiple delays

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Abstract

This paper deals with dynamic behaviors on Hopfield type of ring neural network of four neurons having a pair of short-cut connections with multiple time delays. By suitable transformation and under certain assumptions on multiple time delays, the model is reduced to four dimensional nonlinear delay differential equations with three delays. Regarding these time delays as parameters, delay independent sufficient conditions for no stability switches of the trivial equilibrium of the linearized system are derived. Conditions for stability switching with respect to one delay parameter which is not associated with short-cut connection are obtained. Hopf bifurcations with respect to two other delays which are associated with short-cut connection are also obtained. Using the normal form method and center manifold theory, the direction of the Hopf bifurcation, stability and the properties of Hopf-bifurcating periodic solutions are determined. Using numerical simulations of the nonlinear model, different rich dynamical behaviors such as quasiperiodicity, torus attractor and chaotic-bands are also observed for suitable range of three delay parameters. Lyapunov exponents are also calculated using the AnT 4.669 tool for verification of chaotic dynamics.

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References

  1. Hopfield, J.: Neural network and physical system with emergent collective computational abilities. Proc. Natl. Acad. Sci. USA 79, 2554–2558 (1982)

    Article  MathSciNet  Google Scholar 

  2. Hopfield, J.: Neurons with graded response have collective computational properties like those of two-state neurons. Proc. Natl. Acad. Sci. USA 81, 3088–3092 (1984)

    Article  Google Scholar 

  3. Smaoui, N.: Artificial neural network-based low-dimensional model for spatio-temporally varying cellular frames. Appl. Math. Model. 21, 739–748 (1997)

    Article  MATH  Google Scholar 

  4. Nigrin, A.: Neural Networks for Pattern Recognition. MIT Press, London (1993)

    MATH  Google Scholar 

  5. Seagall, R.S.: Some mathematical and computer modelling of neural networks. Appl. Math. Model. 19, 386–399 (1995)

    Article  MATH  Google Scholar 

  6. Marcus, C.M., Westervelt, R.M.: Stability of analog neural network with delay. Phys. Rev. A 39, 347–359 (1989)

    Article  MathSciNet  Google Scholar 

  7. Baldi, P., Atiya, A.: How delays affect neural dynamics and learning. IEEE Trans. Neural Netw. 5, 612–621 (1994)

    Article  Google Scholar 

  8. Campbell, S.A., Ncube, I., Wu, J.: Multi-stability and stable asynchronous periodic oscillations in a multiple delayed neural system. Physica D 214, 101–119 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  9. Roxin, A., Brunel, N., Hansel, D.: Role of delays in shaping spatiotemporal dynamics of neuronal activity in large networks. Phys. Rev. Lett. 94, 238103 (2005)

    Article  Google Scholar 

  10. Belair, J.: Stability in a model of a delayed of a delayed neural network. J. Dyn. Differ. Equ. 5, 607–623 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  11. Gopalsamy, K., He, X.Z.: Stability in asymmetric Hopfield networks with transmission delays. Physica D 76, 344–358 (1994)

    Article  MathSciNet  Google Scholar 

  12. Olien, L., Belair, J.: Bifurcation, stability and monotonicity properties of a delayed neural network model. Physica D 102, 349–363 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  13. Ruan, S., Wei, J.: Stability and bifurcation in a neural network model with two delays. Physica D 130, 255–272 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  14. Guo, S.J., Huang, L.H.: Hopf bifurcating periodic orbits in a ring of neurons with delays. Physica D 183, 19–44 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  15. Cao, J., Li, X.: Stability in delayed Cohen Grossberg neural networks: LMI optimization approach. Physica D 212, 54–65 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  16. Cao, J., Huang, D., Qu, Y.: Global robust stability of delayed recurrent neural networks. Chaos Solitons Fractals 23, 221–229 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  17. Yu, W., Cao, J.: Stability and Hopf bifurcation analysis on a four-neuron BAM neural network with time delays. Phys. Lett. A 351, 64–78 (2006)

    Article  MATH  Google Scholar 

  18. Yu, W., Cao, J.: Stability and Hopf bifurcation on a two-neuron system with time delay in the frequency domain. Int. J. Bifurc. Chaos Appl. Sci. Eng. 17, 1355–1366 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  19. Liao, X.F., Guo, S.T., Li, C.D.: Stability and bifurcation analysis in tri-neuron model with time delay. Nonlinear Dyn. 49, 319–345 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  20. Yuan, Y.: Dynamics in a delayed neural network. Chaos Solitons Fractals 33, 443–454 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  21. Gupta, P.D., Majee, N.C., Roy, A.B.: Stability, bifurcation and global existence of a Hopf-bifurcating periodic solution for a class of three-neuron delayed network models. Nonlinear Anal. 67, 2934–2954 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  22. Das, A., Roy, A.B., Das, P.: Chaos in a three dimensional general model of neural network. Int. J. Bifur. Chaos 12(10), 2271–2281 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  23. Wei, J., Zhang, C.: Bifurcation analysis of a class of neural networks with delays. Nonlinear Anal. 9(5), 2234–2252 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  24. Yan, X.P.: Bifurcation analysis in a simplified tri-neuron BAM network model with multiple delays. Nonlinear Anal., Real World Appl. 9, 963–976 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  25. Majee, N.C., Roy, A.B.: Temporal dynamics of a two-neuron continuous network model with time delay. Appl. Math. Model. 21, 673–679 (1997)

    Article  MATH  Google Scholar 

  26. Campbell, S.A.: Stability and bifurcation of a simple neural network with multiple time delays. Fields Inst. Commun. 21, 65–79 (1999)

    Google Scholar 

  27. Song, Y., Wei, J., Yuan, Y.: Stability Switches and Hopf bifurcations in a pair of delayed-coupling oscillators. J. Nonlinear Sci. 17, 145–166 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  28. Song, Y., Tadé, M.O., Zhang, T.: Bifurcation analysis and spatio-temporal patterns of nonlinear oscillations in delayed neural network with unidirectional coupling. Nonlinearity 22, 975–1001 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  29. Song, Y., Zhang, T., Tadé, M.O.: Stability Switches, Hopf bifurcations, and spatio-temporal patterns in a delayed neural model with bidirectional coupling. J. Nonlinear Sci. 19(6), 597–632 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  30. Iarosz, K.C., Batista, A.M., Viana, R.L., Lopes, S.R., Caldas, I.L., Penna, T.J.P.: The influence of connectivity on the firing rate in a neuronal network with electrical and chemical synapses. Physica A 391(3), 819–827 (2012)

    Article  Google Scholar 

  31. Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘smallworld’ networks. Nature 393, 440–442 (1998)

    Article  Google Scholar 

  32. Strogatz, S.H.: Exploring complex networks. Nature 410(8), 268–276 (2001)

    Article  Google Scholar 

  33. Xu, X., Liang, Y.C.: Effects of the short-cut connection on the dynamics of a delayed ring neural network. In: Neural networks (IJCNN) (2009)

    Google Scholar 

  34. Mao, X.C., Hu, H.Y.: Stability and Hopf bifurcation of a delayed network of four neurons and a short-cut connection. Int. J. Bifurc. Chaos 18(10), 3053–3072 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  35. Mao, X.C., Hu, H.Y.: Dynamics of a delayed four-neuron network with a short-cut connection: analytical, numerical and experimental studies. Int. J. Nonlinear Sci. Numer. Simul. 10(4), 523–538 (2009)

    Article  Google Scholar 

  36. Mao, X.C., Hu, H.Y.: Hopf bifurcation analysis of a four-neuron network with multiple time delays. Nonlinear Dyn. 55, 95–112 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  37. Pandit, S.A., Amritkar, R.E.: Characterization and control of small-world networks. Phys. Rev. E 60(2), 1119–1122 (1999)

    Article  Google Scholar 

  38. Newman, M.E.J.: The structure and function of complex networks. SIAM Rev. 45, 167–256 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  39. White, J.G., Southgate, E., Thompson, J.N., Brenner, S.: The structure of the nervous system of the nematode C. elegans. Philos. Trans. R. Soc. Lond. 314, 1–340 (1986)

    Article  Google Scholar 

  40. Albert, R., Jeong, H., Barabási, A.-L.: Diameter of the world-wide web. Nature 401, 130–131 (1999)

    Article  Google Scholar 

  41. Felleman, D.J., Van Essen, D.C.: Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1, 1–47 (1991)

    Article  Google Scholar 

  42. Hassard, B.D., Kazarinoff, N.D., Wan, Y.H.: Theory and Application of Hopf Bifurcation. Cambridge University Press, Cambridge (1981)

    Google Scholar 

  43. Gopalsamy, K.: Stability and Oscillations in Delay Differential Equations of Population Dynamics. Kluwer Academic, Dordrecht (1992)

    Book  MATH  Google Scholar 

  44. Hu, H.Y., Wang, Z.H.: Dynamics of Controlled Mechanical Systems with Delayed Feedback. Springer, Heidelberg (2002)

    Book  MATH  Google Scholar 

  45. Hale, J.K., Lungel, S.M.V.: Introduction to Functional Differential Equations. Springer, New York (1993)

    MATH  Google Scholar 

  46. Wang, Z.H., Hu, H.Y.: Stability Switches of time-delayed dynamic systems with unknown parameters. J. Sound Vib. 233(2), 215–233 (2000)

    Article  MATH  Google Scholar 

  47. Sabin, G.C.W., Summers, D.: Chaos in a periodically forced predator-prey ecosystem model. Math. Biosci. 113, 91–113 (1992)

    Article  Google Scholar 

  48. Chilina, S., Hasler, M., Premoli, S.: Fast and accurate calculation of Lyapunov exponents for piecewise-linear system. Int. J. Bifurc. Chaos 4(1), 127–136 (1994)

    Article  Google Scholar 

  49. Wolf, A., Swift, J.B., Swinney, L.H., Vastano, J.A.: Determining Lyapunov exponents from a time series. Physica D 16, 285–317 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  50. Peitgen, H.O., Jurgens, H., Sanpe, D.: Lyapunov Exponents and Chaotic Attractors. In: Chaos and Fractals. New Frontiers of Science, pp. 719–720. Springer, New York (1992)

    Google Scholar 

  51. AnT4669 Avrutin, V., Lammert, R., Schanz, M., Wackenhut, G.: Institute of parallel and distributed systems (IPVS). University of Stuttgart, Germany (1999–2011). http://www.AnT4669.de

  52. Izhikevich, E.M.: Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting. MIT Press, London (2007)

    Google Scholar 

  53. Riecke, H., Roxin, A., Madruga, S., Solla, S.A.: Multiple attractors, long chaotic transients, and failure in small-world networks of excitable neurons. Chaos 17, 026110 (2007)

    Article  MathSciNet  Google Scholar 

  54. Yang, H.H.: Some results on the oscillation of neural networks. In: Proceedings of Nonlinear Theory and Its Applications, Las Vegas, pp. 239–242 (1995)

    Google Scholar 

  55. Ermentrout, B.G., Carson, C.C.: Modeling neural oscillations. Physiol. Behav. 77, 629–633 (2002)

    Article  Google Scholar 

  56. Steriade, M., McCormick, D.A., Sejnowski, T.J.: Thalamocortical oscillations in the sleeping and aroused brain. Science 262, 679–685 (1993)

    Article  Google Scholar 

  57. Gray, C.M.: Synchronous oscillations in neuronal systems: mechanism and functions. J. Comput. Neurosci. 1, 11–38 (1994)

    Article  Google Scholar 

  58. Garfinkel, A., Chen, P.S., Walter, D.O., Karagueuzian, H.S., Kogan, B., Evans, S.J., Karpoukhin, M., Hwang, C., Uchida, T., Gotoh, M., Nwasokwa, O., Sager, P., Weiss, J.N.: Quasiperiodicity and chaos in cardiac fibrillation. J. Clin. Invest. 99(2), 305–314 (1997)

    Article  Google Scholar 

  59. Del Negro, C.A., Wilson, C.G., Butera, R.J., Rigatto, H., Smith, J.C.: Periodicity, mixed-mode oscillations and quasiperiodicity in a rhythm-generating neural network. Biophys. J. 82, 206–214 (2002)

    Article  Google Scholar 

  60. Weyhenmeyer, J., Gallman, E.A.: Rapid Review Neuroscience. Elsevier, Amsterdam (2006)

    Google Scholar 

  61. Paydarfar, D., Forger, D.B., Clay, J.R.: Noisy inputs and the induction of on-off switching behavior in a neuronal pacemaker. J. Neurophysiol. 96, 3338–3348 (2006)

    Article  Google Scholar 

  62. Cameron, I.G., Watanabe, M., Pari, G., Munoz, D.P.: Executive impairment in Parkinson’s disease: response automaticity and task switching. Neuropsychologia 48, 1948–1957 (2010)

    Article  Google Scholar 

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The authors are grateful to anonymous referees for their helpful suggestions to improve the manuscript.

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Kundu, A., Das, P. & Roy, A.B. Complex dynamics of a four neuron network model having a pair of short-cut connections with multiple delays. Nonlinear Dyn 72, 643–662 (2013). https://doi.org/10.1007/s11071-012-0742-2

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