Skip to main content

Advertisement

Log in

Wave pattern stability of neurons coupled by memristive electromagnetic induction

  • Original Paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

During the propagation of action potential, large extracellular potential as well as the difference in the transmembrane potential between adjacent nerve fibers can induce electromagnetic induction current in the neighboring fibers. This can modify the electrical and excitation behaviors of neighboring nerve fibers resulting in interneuronal communication. In this paper, the FitzHugh–Nagumo model is used to describe the local kinetics of the neuronal network and the memristive electromagnetic induction current is included to approach coupling between adjacent nerve fibers. Modulational instability technique is explored both analytically and numerically to bring out some communication features based on nonlinear structures. Through multiple scale expansion in the discrete approximation limit, we show that the dynamics of the network is governed by a well-known differential-difference nonlinear equation. The stability of the plane wave solution revealed the contribution of memristive electromagnetic induction coupling \(K_{0}\) in enhancing interneuronal communication. By exploring the long time evolution of the modulated plane wave via numerical experiments using parameters chosen from the unstable parameter region, the initiation and dynamics of the nonlinear structures agree with the analytical predictions. Extensive numerical experiments revealed the possibility of achieving perfect interneuronal communication using a controlled pitch of magnetic radiation. The results can provide guidance in developing therapy for brain seizure.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Faber, D.S., Korn, H.: Electric field effects: their relevance in central neural networks. Physiol. Rev. 63, 821 (1989)

    Article  Google Scholar 

  2. Maïna, I., Tabi, C.B., et al.: Discrete impulses in emphatically coupled nerve fibers. Neurocomputing 25, 043118 (2015)

    MATH  Google Scholar 

  3. Jefferys, J.G.R.: Nonsynaptic modulation of neuronal activity in the brain: electric currents and extracellular ions. Physiol. Rev. 75, 689 (1995)

    Article  Google Scholar 

  4. Hodgkin, A.L., Huxley, A.F.: A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. (Lond.) 117, 500–544 (1952)

    Article  Google Scholar 

  5. Liang, P.: Neurocomputation by reaction diffusion. Phys. Rev. Lett. 75, 9 (1995)

    Google Scholar 

  6. Takembo, C.N., Mvogo, A., Ekobena, H.P., et al.: Modulated wave formation in myocardial cells under electromagnetic radiation. Int. J. Mod. Phys. B 32, 1850165 (2018)

    Article  MathSciNet  Google Scholar 

  7. Lv, M., Wang, C.N., Ren, G.D., et al.: Model of electrical activity in a neuron under magnetic flow effect. Nonlinear Dyn. 385(85), 1479–1490 (2016)

    Article  Google Scholar 

  8. Lv, M., Ma, J.: Multiple modes of electrical activities of neurons under electromagnetic radiation. Neurocomputing 205, 375–81 (2016)

    Article  Google Scholar 

  9. Strukov, D.B., Snider, G.S., Stewart, D.R., et al.: The missing memristor found. Nature 453, 80–83 (2008)

    Article  Google Scholar 

  10. Mvogo, A., Takembo, C.N., Ekobena, H.P., et al.: Pattern formation in diffusive excitable systems under magnetic flow effects. Phys. Lett. A 381, 2264–2271 (2017)

    Article  MathSciNet  Google Scholar 

  11. Takembo, C.N., Mvogo, A., Ekobena, H.P., et al.: Effect of electromagnetic radiation on the dynamics of spatiotemporal patterns in memristor-based neuronal network. Nonlinear Dyn. (2018). https://doi.org/10.1007/s11071-018-4616-0

    Google Scholar 

  12. Eteme, A.S., Tabi, C.B., Mohamadou, A.: Synchronized nonlinear patterns in electrically coupled Hindmarsh–Rose neural networks with long-range diffusive interactions. Chaos Solitons Fractals 104, 813–826 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  13. Moukam, F.M., Inack, E.M., Yamakou, E.M.: Localized nonlinear excitations in diffusive Hindmarsh–Rose neural networks. Phys. Rev. E 89, 052919 (2014)

    Article  Google Scholar 

  14. Wu, F.Q., Wang, C.N., Xu, Y., et al.: Model of electrical activity in cardiac tissue under electromagnetic induction. Sci. Rep. 6, 28 (2016)

    Article  Google Scholar 

  15. Takembo, C.N., Mvogo, A., Ekobena, H.P., et al.: Localized modulated wave solution in diffusive FitzHugh–Nagumo cardiac network under magnetic flow effect. Nonlinear Dyn. (2018). https://doi.org/10.1007/s11071-018-4617-z

    Google Scholar 

  16. Li, Q.D., Tang, S., et al.: On hyperchaos in a small memristive neural network. Nonlinear Dyn. 78, 1087–1099 (2014)

    Article  MATH  Google Scholar 

  17. Bao, B.C., Qian, H., et al.: Numerical analyses and experimental validations of coexisting multiple attractors in Hopfied neural network. Nonlinear Dyn. 90, 2359–2369 (2017)

    Article  Google Scholar 

  18. Jo, S.H., Chang, T., et al.: Nanoscale memristor device as synapse in neuromorphic systems. Nano Lett. 10, 1297–1301 (2010)

    Article  Google Scholar 

  19. Corinto, F., Ascoli, A., et al.: Memristor synaptic dynamics influence on synchronous behavior of two HindMarsh neurons. In: The 2011 International Joint Conference on Neural Networks(IJCNN), IEEE, pp. 2403-2408 (2011)

  20. Eteme, A.S., Tabi, C.B., Mohamadou, A.: Firing and synchronization modes in neural network under magnetic stimulation. Commun. Nonlinear Sci. Numer. Simul. 72, 432–440 (2019)

    Article  MathSciNet  Google Scholar 

  21. Benjamin, T.B., Feir, J.E.: The disintegration of wave trains on deep water Part 1. Theory. J. Fluid Mech. 27, 417 (1967)

    Article  MATH  Google Scholar 

  22. Remoissenet, M.: Low-amplitude breather and envelope solitons in quasi-one dimensional dimensional physicals model. Phys. Rev. B 33, 2386–2392 (1986)

    Article  Google Scholar 

  23. Villacorta-Atienza, J.A., Makarov, V.A.: Wave-processing of long-scale information by neuronal chains. PLoS ONE 8(2), e57440 (2013)

    Article  Google Scholar 

  24. Brunak, S., Lautrup, B.: Neural Networks. World Scientific Publishing, Singapore (1990)

    Google Scholar 

  25. Hasegawa, A.: Optical solitons in fiber, Springer tract in modern physics, vol. 116. Springer, Berlin (1989)

    Google Scholar 

  26. Wamba, E., Mohamadou, A., Kofané, T.C.: Modulational Instability of a trapped Bose–Einstein condensate with two- and three-body interactions. Phys. Rev. E 77, 046216 (2008)

    Article  Google Scholar 

  27. Ghomsi, P.G., Tameh Berinyoh, T.J., Moukam Kakmeni, F.M.: Ionic wave propagation and collision in an excitable circuit model of microtubules. Chaos 28, 023106 (2018)

    Article  MathSciNet  Google Scholar 

  28. Neiman, A., Schimanskygeier, L., Cornellbell, A.: Noise-enhanced phase syn- chronization in excitable media. Phys. Rev. Lett. 83(23), 4896–9 (1999)

    Article  Google Scholar 

  29. FitzHugh, R.: Impulses and physiological states in theoretical models of nerve membrane. Biophys. J. 1, 445–466 (1961)

    Article  Google Scholar 

  30. Nagumo, J., Arimoto, S., Yoshizawa, S., et al.: An active pulse transmission line simulating nerve axon. Proc. IRE 50, 2061–2070 (1962)

    Article  Google Scholar 

  31. Volos, ChK, Kyprianidis, I.N., et al.: Memristor: a new concept in synchronization of coupled neuromorphic circuits. J. Eng. Sci. Technol. Rev. 8(2), 157–173 (2015)

    Article  Google Scholar 

  32. Leon, J., Manna, M.: Multiscale analysis of discrete nonlinear evolution equations. J. Phys. A Math. Gen. 32, 2845 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  33. Leon, J., Manna, M.: Discrete instability in nonlinear lattices. Phys. Rev. Lett. 83, 2324 (1999)

    Article  Google Scholar 

  34. Tabi, C.B., Mohamadou, M., Kofane, T.C.: Discrete instability in the DNA double helix. Chaos 19, 043101 (2009)

    Article  MATH  Google Scholar 

  35. Kivshar, Y.S., Peyrard, M.: Modulational instability in discrete lattices. Phys. Rev. A 46, 3192 (1992)

    Google Scholar 

  36. Ribeiro, T.L., Copelli, : Deterministic excitable media under Poisson drive: power law responses, spiral waves, and dynamic range. Phys. Rev. E 77, 051911 (2008)

    Article  MathSciNet  Google Scholar 

  37. Lewis, T.: NIMBIOS Workshop on Synchrony, April 11 (2011)

  38. Terman, D., Bose, A., Kopell, N.: Functinal reorganization in thalamocortical networks: transition spindling and delta sleep rhythms. Proc. Natl Acad. Sci. USA 93, 15417–15422 (1996)

    Article  Google Scholar 

  39. Morell, M.J.: Responsive cortical stimulation for the treatment of medically intractable partial epilepsy. Neurology 77, 1295 (2011)

    Article  Google Scholar 

  40. Rubin, J.E., Terman, D.: High frequency stimulation of the subthalamic nucleus eliminates pathological thalamic rhythmicity in a computational model. J. Comput. Neurosci. 16, 211 (2004)

    Article  Google Scholar 

  41. Jiajia, L., Liu, S., et al.: Suppression of firing activities in neuron and neurons of network induced by electromagnetic radiation. Nonlinear Dyn. 83, 801–810 (2018)

    MathSciNet  Google Scholar 

  42. Rostami, Z., Pham, V.T., Jafari, S., et al.: Taking control of initiating wave in a neuronal network using magnetic radiation. Appl. Math. Comput. 336, 141–151 (2018)

    Google Scholar 

  43. Wu, J., Xu, Y., Ma, J.: Levy noise improves the electrical activity in a neuron under electromagnetic radiation. PLoS ONE 12, e0174330 (2017)

    Article  Google Scholar 

  44. Wang, H., Sun, Y., Li, Y., Chen, Y.: Influence of autapse on mode-locking structure of a Hodgkin–Huxley neuron under sinusoidal stimulus. J. Theor. Biol. 358, 25–30 (2014)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to C. N. Takembo.

Ethics declarations

Conflict of interest

The authors of this paper declare that they have no conflict of interest concerning publication of this manuscript.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Takembo, C.N., Mvogo, A., Fouda, H.P.E. et al. Wave pattern stability of neurons coupled by memristive electromagnetic induction. Nonlinear Dyn 96, 1083–1093 (2019). https://doi.org/10.1007/s11071-019-04841-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-019-04841-w

Keywords

Navigation