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Phase synchronization dynamics of coupled neurons with coupling phase in the electromagnetic field

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Abstract

Based on the law of electromagnetic theory, phase synchronization of coupled extended Hindmarsh–Rose neurons with magnetic and electrical couplings is discussed. It is found that the threshold for the coupling strength to reach phase synchronization is gradually smaller when the coupling phase is increased under the same stimulus current. Under the same coupling phase, the coupling strength to reach phase synchronization is almost increasing gradually with increasing the stimulus current, no matter in what state the neuron is. Our recent findings are significant and helpful for further understanding the collective behaviors of neuronal system including comprehensive physical mechanisms and information transmissions.

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References

  1. Pikovsky, A., Rosenblum, M., Kurths, J.: Synchronization: a universal concept in nonlinear sciences. Cambridge University Press, Cambridge (2011)

    MATH  Google Scholar 

  2. Uhlhaas, P.J., Singer, W.: Neural synchrony in brain review disorders: relevance for cognitive dysfunctions and pathophysiology. Neuron 52, 155–168 (2006)

    Article  Google Scholar 

  3. Perc, M., Jordan, J.J., Rand, D.G., Wang, Z., Boccaletti, S., Szolnoki, A.: Statistical physics of human cooperation. Phys. Rep. 687, 1–51 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  4. Helbing, D., Brockmann, D., Chadefaux, T., Donnay, K., Blanke, U., Woolley-Meza, O., Moussaid, Mehdi, Johansson, A., Krause, J., Schutte, S., Perc, M.: Saving human lives: what complexity science and information systems can contribute. J. Stat. Phys. 158, 735–781 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  5. Buzsaki, G.: Rhythms of the Brain. Oxford University Press, Oxford (2011)

    MATH  Google Scholar 

  6. Volos, ChK, Kyprianidis, I.M., Stouboulos, I.N., Tlelo-Cuautle, E., Vaidyanathan, S.: Memristor: a new concept in synchronization of coupled neuromorphic circuits. J. Eng. Sci. Technol. Rev. 8, 157–173 (2015)

    Google Scholar 

  7. Tass, P., Rosenblum, M.G., Weule, J., Kurths, J., Pikovsky, A., Volkmann, J., Schnitzler, A., Freund, H.J.: Detection of n: m phase locking from noisy data: application to magneto- encephalography. Phys. Rev. Lett. 81, 3291 (1998)

    Article  Google Scholar 

  8. Popovych, O.V., Hauptmann, C., Tass, P.A.: Effective synchronisation by nonlinear delayed feedback. Phys. Rev. Lett. 94, 164102 (2005)

    Article  Google Scholar 

  9. Schnitzler, A., Gross, J.: Normal and pathological oscillatory communication in the brain. Nat. Rev. Neurosci. 6, 285–296 (2005)

    Article  Google Scholar 

  10. Zhao, Y., Feng, Z.S.: Desynchronization in synchronous multi-coupled chaotic neurons by mix-adaptive feedback control. J. Biol. Dyn. 7, 1–10 (2013)

    Article  MathSciNet  Google Scholar 

  11. Fan, D.G., Wang, Q.Y.: Improving desynchronization of parkinsonian neuronal network via triplet-structure coordinated reset stimulation. J. Theor. Biol. 370, 157–170 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  12. Wang, Q.Y., Shi, X., Chen, G.R.: Delay-induced synchronization transition in small-world Hodgkin–Huxley neuronal networks with channel blocking. Discrete Contin. Dyn. Syst. B 16, 607–621 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  13. Zhang, H.H., Zheng, Y.H., Su, J.Z., Xiao, P.C.: Seizures dynamics in a neural field model of cortical-thalamic circuitry. Sci. China Technol. Sci. 60, 974–984 (2017)

    Article  Google Scholar 

  14. Hanslmayr, S., Staudigl, T.: How brain oscillations form memories-a processing based perspective on oscillatory subsequent memory effects. Neuroimage 85, 648–655 (2014)

    Article  Google Scholar 

  15. Tallon-Baudry, C., Bertrand, O., Peronnet, F., Pernier, J.: Induced gamma-band activity during the delay of a visual short-term memory task in humans. J. Neurosci. 18, 4244–4254 (1998)

    Article  Google Scholar 

  16. Schneider, S.L., Rose, M.: Intention to encode boosts memory-related pre-stimulus EEG beta power. Neuroimage 125, 978–987 (2016)

    Article  Google Scholar 

  17. Tallon-Baudry, C., Bertrand, O., Fischer, C.: Oscillatory synchrony between human extrastriate areas during visual short-term memory maintenance. J. Neurosci. 21(RC177), 1–5 (2001)

    Google Scholar 

  18. Kyrychko, Y.N., Blyuss, K.B., Schöll, E.: Amplitude and phase dynamics in oscillators with distributed-delay coupling. Phil. Trans. R. Soc. A 371, 20120466 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  19. Roux, F., Uhlhaas, P.J.: Working memory and neural oscillations: alpha–gamma versus theta–gamma codes for distinct WM information? Trends Cognit. Sci. 18, 16–25 (2014)

    Article  Google Scholar 

  20. Daume, J., Gruber, T., Engel, A.K., Friese, U.: Phase-amplitude coupling and long-range phase synchronization reveal frontotemporal interactions during visual working memory. J. Neurosci. 37, 313–322 (2017)

    Article  Google Scholar 

  21. Ivanchenko, M.V., Osipov, G.V., Shalfeev, V.D., Kurths, J.: Phase synchronization in ensembles of bursting oscillators. Phys. Rev. Lett. 93, 134101 (2004)

    Article  Google Scholar 

  22. Yu, H.T., Wang, J., Deng, B., Wei, X.l, Wong, Y.K., Chan, W.L., Tsang, K.M., Yu, Z.Q.: Chaotic phase synchronization in small-world networks of bursting neurons. Chaos 21, 013127 (2011)

    Article  MathSciNet  Google Scholar 

  23. Sun, X.J., Perc, M., Kurths, J.: Effects of partial time delays on phase synchronization in Watts–Strogatz small-world neuronal networks. Chaos 27, 053113 (2017)

    Article  MathSciNet  Google Scholar 

  24. Ma, J., Lv, M., Zhou, P., Xu, Y., Tasawar, H.: Phase synchronization between two neurons induced by coupling of electromagnetic field. Appl. Math. Comput. 307, 321–328 (2017)

    MathSciNet  Google Scholar 

  25. Wang, H.X., Wang, Q.Y., Zheng, Y.H.: Bifurcation analysis for Hindmarsh–Rose neuronal model with time-delayed feedback control and application to chaos control. Sci. China Technol. Sci. 57, 872–878 (2014)

    Article  MathSciNet  Google Scholar 

  26. Wang, Q.Y., Chen, G.R.: Delay-induced intermittent transition of synchronization in neuronal networks with hybrid synapses. Chaos. 21, 013123 (2011)

    Article  Google Scholar 

  27. Wang, Q.Y., Chen, G., Perc, M.: Synchronous bursts on scale-free neuronal networks with attractive and repulsive coupling. PLoS ONE 6, e15851 (2011)

    Article  Google Scholar 

  28. Yu, H.T., Wang, J., Du, J.W., Deng, B., Wei, X.L.: Local and global synchronization transitions induced by time delays in small-world neuronal networks with chemical synapses. Cognit. Neurodyn. 9, 93–101 (2015)

    Article  Google Scholar 

  29. Wang, Q.Y., Duan, Z.S., Perc, M.: Synchronization transitions on small-world neuronal networks: effects of information transmission delay and rewiring probability. EPL 83, 50008 (2008)

  30. Wang, Q.Y., Perc, M., Duan, Z.S., Chen, G.R.: Synchronization transitions on scale-free neuronal networks due to finite information transmission delays. Phys. Rev. E 80, 026206 (2009)

    Article  Google Scholar 

  31. Lv, M., Ma, J.: Model of electrical activity in a neuron under magnetic flow effect. Nonlinear Dyn. 85, 1479–1490 (2016)

    Article  Google Scholar 

  32. Ren, G.D., Xu, Y., Wang, C.N.: Synchronization behavior of coupled neuron circuits composed of memristors. Nonlinear Dyn. 88, 893–901 (2017)

    Article  Google Scholar 

  33. Xu, Y., Jia, Y., Ma, J., Tasawar, H., Ahmed, A.: Collective responses in electrical activities of neurons under field coupling. Sci. Rep. 8, 1349 (2018)

    Article  Google Scholar 

  34. Xu, Y., Ying, H.P., Jia, Y., Ma, J., Tasawar, H.: Autaptic regulation of electrical activities in neuron under electromagnetic induction. Sci. Rep. 7, 43452 (2017)

    Article  Google Scholar 

  35. Guo, S., Xu, Y., Wang, C., Jin, W., Aatef, Hobiny, Ma, Jun: Collective response, synapse coupling and field coupling in neuronal network. Chaos Solitons Fractals 105, 120–127 (2017)

    Article  MathSciNet  Google Scholar 

  36. Wang, C.N., Ma, J.: A review and guidance for pattern selection in spatiotemporal system. Int. J. Mod. Phys. B 32, 1830003 (2018)

    Article  MathSciNet  Google Scholar 

  37. Wang, H.T., Chen, Y.: Spatiotemporal activities of neural network exposed to external electric fields. Nonlinear Dyn. 85, 881–891 (2016)

    Article  MathSciNet  Google Scholar 

  38. Omelchenko, I., Omel’chenko, O.E., Hövel, P., Schöll, E.: When nonlocal coupling between oscillators becomes stronger: patched synchrony or multichimera states. Phys. Rev. Lett. 110, 224101 (2013)

    Article  Google Scholar 

  39. Hizanidis, J., Kanas, V.G., Bezerianos, A., Bountis, T.: Chimera states in networks of nonlocally coupled Hindmarsh–Rose neuron models. Int. J. Bifurc. Chaos 24, 450030-1–450030-9 (2014)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

This work is support by the National Natural Science Foundation of China (Grant No. 11502073) and Scientific Research Fund of Henan Provincial Education Department (Grant No. 14A110004) and Doctoral Foundation of Henan Polytechnic University (Grant No. B2012-107).

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Correspondence to Yong Zhao.

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Zhao, Y., Sun, X., Liu, Y. et al. Phase synchronization dynamics of coupled neurons with coupling phase in the electromagnetic field. Nonlinear Dyn 93, 1315–1324 (2018). https://doi.org/10.1007/s11071-018-4261-7

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  • DOI: https://doi.org/10.1007/s11071-018-4261-7

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