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Reliability of Coupled Oscillators

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Abstract

We study the reliability of phase oscillator networks in response to fluctuating inputs. Reliability means that an input elicits essentially identical responses upon repeated presentations, regardless of the network’s initial condition. Single oscillators are well known to be reliable. We show in this paper that unreliable behavior can occur in a network as small as a coupled oscillator pair in which the signal is received by the first oscillator and relayed to the second with feedback. A geometric explanation based on shear-induced chaos at the onset of phase-locking is proposed. We treat larger networks as decomposed into modules connected by acyclic graphs, and give a mathematical analysis of the acyclic parts. Moreover, for networks in this class, we show how the source of unreliability can be localized, and address questions concerning downstream propagation of unreliability once it is produced.

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References

  • Arnold, L.: Random Dynamical Systems. Springer, New York (2003)

    Google Scholar 

  • Arnold, L., Imkeller, P., Sri Namachchivaya, N.: The asymptotic stability of a noisy non-linear oscillator. J. Sound Vib. 269, 1003–1029 (2004)

    Article  MathSciNet  Google Scholar 

  • Baxendale, P.H.: Stability and equilibrium properties of stochastic flows of diffeomorphisms. In: Progress Probab., vol. 27. Birkhauser, Boston (1992)

    Google Scholar 

  • Baxendale, P.H., Goukasian, L.: Lyapunov exponents for small perturbations of Hamiltonian systems. Ann. Probab. 30(1), 101–134 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  • Brown, E., Holmes, P., Moehlis, J.: Globally coupled oscillator networks. In: Kaplan, E., Marsden, J.E., Sreenivasan, K.R. (eds.) Problems and Perspectives in Nonlinear Science: A Celebratory Volume in Honor of Lawrence Sirovich, pp. 183–215. Springer, New York (2003)

    Google Scholar 

  • Bryant, H.L., Segundo, J.P.: Spike initiation by transmembrane current: a white-noise analysis. J. Physiol. 260, 279–314 (1976)

    Google Scholar 

  • Chow, C.C.: Phase-locking in weakly heterogeneous neuronal networks. Physica D 118, 343–370 (1998)

    Article  MathSciNet  Google Scholar 

  • Eckmann, J.-P., Ruelle, D.: Ergodic theory of chaos and strange attractors. Rev. Mod. Phys. 57, 617–656 (1985)

    Article  MathSciNet  Google Scholar 

  • Ermentrout, G.B.: n:m phase locking of weakly coupled oscillators. J. Math. Biol. 12, 327–342 (1981)

    Article  MathSciNet  MATH  Google Scholar 

  • Ermentrout, G.B.: Neural networks as spatio-temporal pattern-forming systems. Rep. Prog. Phys. 61, 353–430 (1991)

    Article  Google Scholar 

  • Ermentrout, G.B.: Type I membranes, phase resetting curves, and synchrony. Neural Comput. 8, 979–1001 (1996)

    Article  Google Scholar 

  • Ermentrout, G.B., Kopell, N.: Multiple pulse interactions and averaging in coupled neural oscillators. J. Math. Biol. 29, 195–217 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  • Gerstner, W., van Hemmen, J.L., Cowan, J.D.: What matters in neuronal locking?. Neural Comput. 8(8), 1653–1676 (1996)

    Article  Google Scholar 

  • Goldobin, D., Pikovsky, A.: Synchronization and desynchronization of self-sustained oscillators by common noise. Phys. Rev. E 71, 045201–045204 (2005)

    Article  MathSciNet  Google Scholar 

  • Goldobin, D., Pikovsky, A.: Antireliability of noise-driven neurons. Phys. Rev. E 73, 061906-1–061906-4 (2006)

    Article  MathSciNet  Google Scholar 

  • Guckenheimer, J.: Isochronous and phaseless sets. J. Math. Biol. 1, 259–273 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  • Guckenheimer, J., Holmes, P.: Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields. Springer, Berlin (1983)

    MATH  Google Scholar 

  • Gutkin, B., Ermentrout, G.B., Rudolph, M.: Spike generating dynamics and the conditions for spike-time precision in cortical neurons. J. Comput. Neurosci. 15, 91–103 (2003)

    Article  Google Scholar 

  • Hansel, D., Mato, G., Meunier, C.: Synchrony in excitatory neural networks. Neural Comput. 7, 307–337 (1995)

    Article  Google Scholar 

  • Herz, A.V., Hopfield, J.J.: Earthquake cycles and neural reverberations: collective oscillations in systems with pulse-coupled threshold elements. Phys. Rev. Lett. 75, 1222–1225 (1995)

    Article  Google Scholar 

  • Hoppensteadt, F.C., Izhikevich, E.M.: Weakly Connected Neural Networks. Springer, New York (1997)

    Google Scholar 

  • Kifer, Yu.: Ergodic Theory of Random Transformations. Birkhauser, Boston (1986)

    MATH  Google Scholar 

  • Kosmidis, E., Pakdaman, K.: Analysis of reliability in the Fitzhugh–Nagumo neuron model. J. Comput. Neurosci. 14, 5–22 (2003)

    Article  Google Scholar 

  • Kozachenko, L.F., Leonenko, N.N.: Sample estimate of the entropy of a random vector. Probl. Inf. Transm. 23 (1987)

  • Kunita, H.: Stochastic flows and stochastic differential equations. Cambridge Studies in Advanced Mathematics, vol. 24. Cambridge University Press, Cambridge (1990)

    MATH  Google Scholar 

  • Kuramoto, Y.: Phase- and center-manifold reductions for large populations of coupled oscillators with application to non-locally coupled systems. Int. J. Bifurc. Chaos 7, 789–805 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  • Le Jan, Y.: Équilibre statistique pour les produits de difféomorphismes aléatoires indépendants. Ann. Inst. H. Poincaré Probab. Stat. 23(1), 111–120 (1987)

    MathSciNet  MATH  Google Scholar 

  • Ledrappier, F., Young, L.-S.: Entropy formula for random transformations. Probab. Theory Relat. Fields 80, 217–240 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  • Lin, K.K., Young, L.-S.: Shear-induced chaos. Nonlinearity 21, 899–922 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  • Mainen, Z., Sejnowski, T.: Reliability of spike timing in neocortical neurons. Science 268, 1503–1506 (1995)

    Article  Google Scholar 

  • Mattila, P.: Geometry of Sets and Measures in Euclidean Space. Cambridge University Press, Cambridge (1995)

    Google Scholar 

  • Nakao, H., Arai, K., Nagai, K., Tsubo, Y., Kuramoto, Y.: Synchrony of limit-cycle oscillators induced by random external impulses. Phys. Rev. E 72, 026220-1–026220-13 (2005)

    Article  MathSciNet  Google Scholar 

  • Nualart, D.: The Malliavin Calculus and Related Topics. Springer, Berlin (2006)

    MATH  Google Scholar 

  • Nunes, A.M., Pereira, J.V.: Phase-locking of two Andronov clocks with a general interaction. Phys. Lett. A 107, 362–366 (1985)

    Article  Google Scholar 

  • Pakdaman, K., Mestivier, D.: External noise synchronizes forced oscillators. Phys. Rev. E 64, 030901–030904 (2001)

    Article  Google Scholar 

  • Peskin, C.S.: Mathematical Aspects of Heart Physiology. Courant Institute of Mathematical Sciences, New York (1988)

    Google Scholar 

  • Pikovsky, A., Rosenblum, M., Kurths, J.: Synchronization: A Universal Concept in Nonlinear Sciences. Cambridge University Press, Cambridge (2001)

    MATH  Google Scholar 

  • Popovych, O.V., Maistrenko, Y.L., Tass, P.A.: Phase chaos in coupled oscillators. Phys. Rev. E 71, 065201-1–065201-4 (2005)

    Article  MathSciNet  Google Scholar 

  • Rinzel, J., Ermentrout, G.B.: Analysis of neural excitability and oscillations. In: Koch, C., Segev, I. (eds.) Methods in Neuronal Modeling, pp. 251–291. MIT Press, Cambridge (1998)

    Google Scholar 

  • Ritt, J.: Evaluation of entrainment of a nonlinear neural oscillator to white noise. Phys. Rev. E 68, 041915–041921 (2003)

    Article  MathSciNet  Google Scholar 

  • Strogatz, S.: From Kuramoto to Crawford: Exploring the onset of synchronization in populations of coupled oscillators. Physica D 143, 1–20 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  • Strogatz, S., Mirollo, R.: Synchronization of pulse-coupled biological oscillators. SIAM J. Appl. Math. 50, 1645–1662 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  • Taylor, D., Holmes, P.: Simple models for excitable and oscillatory neural networks. J. Math. Biol. 37, 419–446 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  • Teramae, J., Fukai, T.: Reliability of temporal coding on pulse-coupled networks of oscillators (2007). arXiv:0708.0862v1 [nlin.AO]

  • Teramae, J., Tanaka, D.: Robustness of the noise-induced phase synchronization in a general class of limit cycle oscillators. Phys. Rev. Lett. 93, 204103–204106 (2004)

    Article  Google Scholar 

  • Victor, J.D.: Binless strategies for estimation of information from neural data. Phys. Rev. E 66 (2002)

  • Wang, Q., Young, L.-S.: Strange attractors with one direction of instability. Commun. Math. Phys. 218, 1–97 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  • Wang, Q., Young, L.-S.: From invariant curves to strange attractors. Commun. Math. Phys. 225, 275–304 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  • Wang, Q., Young, L.-S.: Strange attractors in periodically-kicked limit cycles and Hopf bifurcations. Commun. Math. Phys. 240, 509–529 (2003)

    MathSciNet  MATH  Google Scholar 

  • Wang, Q., Young, L.-S.: Toward a theory of rank one attractors. Ann. Math. (2009, to appear)

  • Winfree, A.: Patterns of phase compromise in biological cycles. J. Math. Biol. 1, 73–95 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  • Winfree, A.: The Geometry of Biological Time. Springer, New York (2001)

    MATH  Google Scholar 

  • Young, L.-S.: Ergodic theory of differentiable dynamical systems. In: Real and Complex Dynamics. NATO ASI Series, pp. 293–336. Kluwer Academic, Dordrecht (1995)

    Google Scholar 

  • Young, L.-S.: What are SRB measures, and which dynamical systems have them? J. Stat. Phys. 108(5), 733–754 (2002)

    Article  MATH  Google Scholar 

  • Zaslavsky, G.: The simplest case of a strange attractor. Phys. Lett. A 69(3), 145–147 (1978)

    Article  MathSciNet  Google Scholar 

  • Zhou, C., Kurths, J.: Noise-induced synchronization and coherence resonance of a Hodgkin–Huxley model of thermally sensitive neurons. Chaos 13, 401–409 (2003)

    Article  Google Scholar 

Download references

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Correspondence to Kevin K. Lin.

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Lin, K.K., Shea-Brown, E. & Young, LS. Reliability of Coupled Oscillators. J Nonlinear Sci 19, 497–545 (2009). https://doi.org/10.1007/s00332-009-9042-5

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