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Lotka–Volterra Like Dynamics in Phase Oscillator Networks

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Advances in Dynamics, Patterns, Cognition

Part of the book series: Nonlinear Systems and Complexity ((NSCH,volume 20))

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Abstract

Many neural processes, including higher order cognitive functions, are characterized by metastable rather than attractor dynamics. Generalized Lotka–Volterra equations provide a suitable model that can give rise to switching dynamics between metastable equilibria and we review some results how such models can predict bounds on neural processing capacity. In this context generalized Lotka–Volterra system describes the interaction of macroscopic quantities rather than individual neural oscillators. We indicate a connection between generalized Lotka–Volterra equations and the mean field dynamics of networks of multiple identical populations of phase oscillators. This relationship not only gives insight into the global dynamics of phase oscillator populations but also hints at how spatiotemporal dynamics of synchronization can arise in phase oscillator networks.

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References

  1. Abeles, M., Bergman, H., Gat, I., Meilijson, I., Seidemann, E., Tishby, N., Vaadia, E.: Cortical activity flips among quasi-stationary states. Proc. Natl. Acad. Sci. USA 92 (19), 8616–8620 (1995)

    Article  Google Scholar 

  2. Abrams, D.M., Mirollo, R.E., Strogatz, S.H., Wiley, D.A.: Solvable model for chimera states of coupled oscillators. Phys. Rev. Lett. 101 (8), 084103 (2008)

    Article  Google Scholar 

  3. Acebrón, J., Bonilla, L., Pérez Vicente C., Ritort, F., Spigler, R.: The Kuramoto model: a simple paradigm for synchronization phenomena. Rev. Mod. Phys. 77 (1), 137–185 (2005)

    Article  Google Scholar 

  4. Afraimovich, V.S., Rabinovich, M.I., Varona, P.: Heteroclinic contours in neural ensembles and the winnerless competition principle. Int. J. Bifurcation Chaos 14 (4), 1195–1208 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  5. Afraimovich, V.S., Zhigulin, V.P., Rabinovich, M.I.: On the origin of reproducible sequential activity in neural circuits. Chaos 14 (4), 1123–1129 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  6. Ashwin, P., Burylko, O.: Weak chimeras in minimal networks of coupled phase oscillators. Chaos 25, 013106 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  7. Bick, C.: Isotropy of angular frequencies and weak chimeras with broken symmetry. J. Nonlinear Sci. 27 (2), 605–626 (2017). http://doi.org/10.1007/s00332-016-9345-2

    Article  MathSciNet  Google Scholar 

  8. Bick, C., Ashwin, P.: Chaotic weak chimeras and their persistence in coupled populations of phase oscillators. Nonlinearity 29 (5), 1468–1486 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  9. Bick, C., Martens, E.A.: Controlling chimeras. New J. Phys. 17 (3), 033030 (2015)

    Article  MathSciNet  Google Scholar 

  10. Bick, C., Rabinovich, M.I.: Dynamical origin of the effective storage capacity in the brain’s working memory. Phys. Rev. Lett. 103 (21), 218101 (2009)

    Article  Google Scholar 

  11. Bick, C., Rabinovich, M.I.: On the occurrence of stable heteroclinic channels in Lotka-Volterra models. Dyn. Syst. 25 (1), 97–110 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  12. Friston, K.J.: Transients, metastability, and neuronal dynamics. NeuroImage 5 (2), 164–171 (1997)

    Article  Google Scholar 

  13. Golubitsky, M., Stewart, I.: The Symmetry Perspective. Progress in Mathematics, vol. 200. Birkhäuser, Basel (2002)

    Google Scholar 

  14. Komarov, M., Pikovsky, A.: Effects of nonresonant interaction in ensembles of phase oscillators. Phys. Rev. E 84 (1), 16210 (2011)

    Article  Google Scholar 

  15. Kuramoto, Y.: Chemical Oscillations, Waves, and Turbulence. Springer Series in Synergetics, vol. 19. Springer, Berlin (1984)

    Google Scholar 

  16. Kuramoto, Y., Battogtokh, D.: Coexistence of coherence and incoherence in nonlocally coupled phase oscillators. Nonlinear Phenom. Complex Syst. 5 (4), 380–385 (2002)

    Google Scholar 

  17. Laing, C.R.: Chimera states in heterogeneous networks. Chaos 19 (1), 013113 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  18. Laing, C.R.: The dynamics of chimera states in heterogeneous Kuramoto networks. Physica D 238 (16), 1569–1588 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  19. Laing, C.R.: Disorder-induced dynamics in a pair of coupled heterogeneous phase oscillator networks. Chaos 22 (4), 043104 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  20. Martens, E.A.: Bistable chimera attractors on a triangular network of oscillator populations. Phys. Rev. E 82 (1), 016216 (2010)

    Article  MathSciNet  Google Scholar 

  21. Martens, E.A., Panaggio, M.J., Abrams, D.M.: Basins of attraction for chimera states. New J. Phys. 18 (2), 022002 (2016)

    Article  Google Scholar 

  22. Martens, E.A., Bick, C., Panaggio, M.J.: Chimera states in two populations with heterogeneous phase-lag. Chaos 26 (9), 094819 (2016)

    Article  MathSciNet  Google Scholar 

  23. May, R.M., Leonard, W.J.: Nonlinear aspects of competition between three species. SIAM J. Appl. Math. 29 (2), 243–253 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  24. Miller, G.: The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol. Rev. 63, 81–97 (1956)

    Article  Google Scholar 

  25. Montbrió, E., Kurths, J., Blasius, B.: Synchronization of two interacting populations of oscillators. Phys. Rev. E 70 (5), 056125 (2004)

    Article  Google Scholar 

  26. Nowotny, T., Rabinovich, M.I.: Dynamical origin of independent spiking and bursting activity in neural microcircuits. Phys. Rev. Lett. 98 (12), 1–4 (2007)

    Article  Google Scholar 

  27. Orosz, G., Moehlis, J., Ashwin, P.: Designing the dynamics of globally coupled oscillators. Prog. Theor. Phys. 122 (3), 611–630 (2009)

    Article  MATH  Google Scholar 

  28. Ott, E., Antonsen, T.M.: Low dimensional behavior of large systems of globally coupled oscillators. Chaos 18 (3), 037113 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  29. Ott, E., Antonsen, T.M.: Long time evolution of phase oscillator systems. Chaos 19 (2), 023117 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  30. Ott, E., Hunt, B.R., Antonsen, T.M.: Comment on “Long time evolution of phase oscillator systems” [Chaos 19, 023117 (2009)]. Chaos 21 (2), 025112 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  31. Panaggio, M.J., Abrams, D.M.: Chimera states: coexistence of coherence and incoherence in networks of coupled oscillators. Nonlinearity 28 (3), R67–R87 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  32. Pikovsky, A., Rosenblum, M.: Partially integrable dynamics of hierarchical populations of coupled oscillators. Phys. Rev. Lett. 101 (26), 1–4 (2008)

    Article  Google Scholar 

  33. Rabinovich, M.I., Varona, P., Selverston, A., Abarbanel, H.D.I.: Dynamical principles in neuroscience. Rev. Mod. Phys. 78 (4), 1213–1265 (2006)

    Article  Google Scholar 

  34. Rabinovich, M.I., Huerta, R., Laurent, G.: Transient dynamics for neural processing. Science 321 (5885), 48–50 (2008)

    Article  Google Scholar 

  35. Rabinovich, M.I., Afraimovich, V.S., Bick, C., Varona, P.: Information flow dynamics in the brain. Phys. Life Rev. 9 (1), 51–73 (2012)

    Article  Google Scholar 

  36. Rabinovich, M.I., Simmons, A.N., Varona, P.: Dynamical bridge between brain and mind. Trends Cogn. Sci. 19 (8), 453–461 (2015)

    Article  Google Scholar 

  37. Sakaguchi, H., Kuramoto, Y.: A soluble active rotater model showing phase transitions via mutual entertainment. Prog. Theor. Phys. 76 (3), 576–581 (1986)

    Article  Google Scholar 

  38. Strogatz, S.H.: From Kuramoto to Crawford: exploring the onset of synchronization in populations of coupled oscillators. Physica D 143 (1–4), 1–20 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  39. Tognoli, E., Scott Kelso, J.A.: The metastable brain. Neuron 81 (1), 35–48 (2014)

    Article  Google Scholar 

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Acknowledgements

The author is indebted to M.I. Rabinovich for his guidance and support over the years. Moreover, he would like to thank P. Ashwin and E.A. Martens for many helpful discussions. This work has received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007–2013) under REA grant agreement no. 626111.

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Bick, C. (2017). Lotka–Volterra Like Dynamics in Phase Oscillator Networks. In: Aranson, I., Pikovsky, A., Rulkov, N., Tsimring, L. (eds) Advances in Dynamics, Patterns, Cognition. Nonlinear Systems and Complexity, vol 20. Springer, Cham. https://doi.org/10.1007/978-3-319-53673-6_8

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  • DOI: https://doi.org/10.1007/978-3-319-53673-6_8

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