Skip to main content

Multirhythmicity for a Time-Delayed FitzHugh-Nagumo System with Threshold Nonlinearity

  • Chapter
  • First Online:
Control of Self-Organizing Nonlinear Systems

Part of the book series: Understanding Complex Systems ((UCS))

Abstract

A time-delayed FitzHugh-Nagumo (FHN) system exhibiting a threshold nonlinearity is studied both experimentally and theoretically. The basic steady state is stable but distinct stable oscillatory regimes may coexist for the same values of parameters (multirhythmicity). They are characterized by periods close to an integer fraction of the delay. From an asymptotic analysis of the FHN equations, we show that the mechanism leading to those oscillations corresponds to a limit-point of limit-cycles. In order to investigate their robustness with respect to noise, we study experimentally an electrical circuit that is modeled mathematically by the same delay differential equations. We obtain quantitative agreements between numerical and experimental bifurcation diagrams for the different coexisting time-periodic regimes.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. J. Keener, J. Sneyd, Mathematical Physiology (Springer, 1998)

    Google Scholar 

  2. C. Fall, Computational Cell Biology (Springer, 2002)

    Google Scholar 

  3. B. Ermentrout, D. Terman, Mathematical Foundations of Neuroscience (Springer, 2002)

    Google Scholar 

  4. A.L. Hodgkin, A.F. Huxley, J. Physiol. 117(4), 500 (1952)

    Article  Google Scholar 

  5. R. FitzHugh, Biophys. J. 1(6), 445 (1961)

    Article  ADS  Google Scholar 

  6. J. Nagumo, S. Arimoto, S. Yoshizawa, Proc IRE 50(10), 2061 (1962)

    Article  Google Scholar 

  7. E. Schöll, G. Hiller, P. Hövel, M. Dahlem, Philos. Trans. R. Soc. London Ser. A 367(1891), 1079 (2009). doi:10.1098/rsta.2008.0258. http://rsta.royalsocietypublishing.org/content/367/1891/1079.abstract

    Google Scholar 

  8. W.J. Freeman, Int. J. Bifurcat. Chaos 10(10), 2307 (2000)

    Article  Google Scholar 

  9. S. Kim, S.H. Park, C.S. Ryu, Phys. Rev. Lett. 79, 2911 (1997). doi:10.1103/PhysRevLett.79.2911

    Article  ADS  Google Scholar 

  10. M.K.S. Yeung, S.H. Strogatz, Phys. Rev. Lett. 82, 648 (1999). doi:10.1103/PhysRevLett.82.648

    Article  ADS  Google Scholar 

  11. M.Y. Choi, H.J. Kim, D. Kim, H. Hong, Phys. Rev. E 61, 371 (2000). doi:10.1103/PhysRevE.61.371

    Article  ADS  Google Scholar 

  12. W.S. Lee, E. Ott, T.M. Antonsen, Phys. Rev. Lett. 103, 044101 (2009). doi:10.1103/PhysRevLett.103.044101

    Article  ADS  Google Scholar 

  13. G. Deco, V. Jirsa, A. McIntosh, O. Sporns, R. Kötter, Proc. Nat. Acad. Sci. 106(25), 10302 (2009)

    Article  ADS  Google Scholar 

  14. G. Deco, V.K. Jirsa, J. Neurosci. 32(10), 3366 (2012)

    Article  Google Scholar 

  15. R. Ton, G. Deco, A. Daffertshofer, PLoS Comput. Biol. 10(7), e1003736 (2014)

    Article  ADS  Google Scholar 

  16. C. Cakan, J. Lehnert, E. Schöll (2013). arXiv:1311.1919

  17. N. Burić, D. Todorović, Phys. Rev. E 67, 066222 (2003). doi:10.1103/PhysRevE.67.066222

    Article  ADS  MathSciNet  Google Scholar 

  18. M. Dahlem, G. Hiller, A. Panchuk, E. Schöll, Int. J. Bifurcat. Chaos 19(02), 745 (2009). doi:10.1142/S0218127409023111

    Article  Google Scholar 

  19. O. Vallès-Codina, R. Möbius, S. Rüdiger, L. Schimansky-Geier, Phys. Rev. E 83, 036209 (2011). doi:10.1103/PhysRevE.83.036209

    Article  ADS  MathSciNet  Google Scholar 

  20. L. Weicker, T. Erneux, L. Keuninckx, J. Danckaert, Phys. Rev. E 89, 012908 (2014). doi:10.1103/PhysRevE.89.012908

    Article  ADS  Google Scholar 

  21. P. Hövel, Control of complex nonlinear systems with delay. Ph.D. Thesis, Technischen Universität Berlin (2010)

    Google Scholar 

  22. T. Prager, H.P. Lerch, L. Schimansky-Geier, E. Schöll, J. Phys. A Math. Theor. 40(36), 11045 (2007)

    Article  ADS  Google Scholar 

  23. N.B. Janson, A.G. Balanov, E. Schöll, Phys. Rev. Lett. 93, 010601 (2004). doi:10.1103/PhysRevLett.93.010601

    Article  ADS  Google Scholar 

  24. A. Balanov, N.B. Janson, E. Schöll, Physica D 199(1), 1 (2004)

    Article  ADS  Google Scholar 

  25. J. Rinzel, J.B. Keller, Biophys. J. 13(12), 1313 (1973). doi:10.1016/S0006-3495(73)86065-5. http://www.sciencedirect.com/science/article/pii/S0006349573860655

    Google Scholar 

  26. S. Coombes, Physica D 160, 173 (2011)

    Article  ADS  MathSciNet  Google Scholar 

  27. S. Coombes, C. Laing, Physica D 238(3), 264 (2009). doi:10.1016/j.physd.2008.10.014. http://www.sciencedirect.com/science/article/pii/S0167278908003692

    Google Scholar 

  28. T. Erneux, Applied Delay Differential Equations (Springer, New York, 2009)

    MATH  Google Scholar 

  29. S. Yanchuk, P. Perlikowski, Phys. Rev. E 79, 046221 (2009). doi:10.1103/PhysRevE.79.046221

    Article  ADS  MathSciNet  Google Scholar 

  30. L. Weicker, T. Erneux, D.P. Rosin, D.J. Gauthier, Phys. Rev. E 91, 012910 (2015). doi:10.1103/PhysRevE.91.012910

    Article  ADS  Google Scholar 

  31. G. Friart, G. Verschaffelt, J. Danckaert, T. Erneux, Opt. Lett. 39(21), 6098 (2014). doi:10.1364/OL.39.006098

    Article  ADS  Google Scholar 

Download references

Acknowledgments

L.W. acknowledges the Belgian F.R.I.A., the Conseil Régional de Lorraine, and the Agence Nationale de la Recherche (ANR) TINO project (ANR-12-JS03-005). G.F. acknowledges the Belgian F.R.I.A. T.E. acknowledges the support of the F.N.R.S. This work also benefited from the support of the Belgian Science Policy Office under Grant No IAP-7/35.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gaetan Friart .

Editor information

Editors and Affiliations

Appendices

Appendix

A Connection at \(t=t_{1}\) and \(t=t_{2}\)

We first require that the solutions (17.9)–(17.10) and (17.13)–(17.14) are equal at the critical times \(t=t_{1}\) and \( t=t_{2}\). This leads to the following four equations

$$\begin{aligned} C+D&=Ae^{\lambda _{+}t_{1}}+Be^{\lambda _{-}t_{1}}, \end{aligned}$$
(17.31)
$$\begin{aligned} 1-(1+\varepsilon \lambda _{+})Ae^{\lambda _{+}t_{1}}-(1+\varepsilon \lambda _{-})Be^{\lambda _{-}t_{1}}&=-(1+\varepsilon \lambda _{+})C-(1+\varepsilon \lambda _{-})D, \end{aligned}$$
(17.32)
$$\begin{aligned} Ce^{\lambda _{+}t_{21}}+De^{\lambda _{-}t_{21}}&=A+B, \end{aligned}$$
(17.33)
$$\begin{aligned} -(1+\varepsilon \lambda _{+})Ce^{\lambda _{+}t_{21}}-(1+\varepsilon \lambda _{-})De^{\lambda _{-}t_{21}}&=1-(1+\varepsilon \lambda _{+})A-(1+\varepsilon \lambda _{-})B, \end{aligned}$$
(17.34)

where \(t_{21}\equiv t_{2}-t_{1}\). We now determine the constants A, B, C, and D as functions of \(t_{1}\) and \(t_{2}\).

From Eqs. (17.31) and (17.33), we determine

$$\begin{aligned} Ae^{\lambda _{+}t_{1}}&=C+D-Be^{\lambda _{-}t_{1}}, \end{aligned}$$
(17.35)
$$\begin{aligned} Ce^{\lambda _{+}t_{21}}&=A+B-De^{\lambda _{-}t_{21}}. \end{aligned}$$
(17.36)

Inserting these expressions of \(A\exp (\lambda _{+}t_{1})\) and \(C\exp (\lambda _{+}t_{21})\) into Eqs. (17.32) and (17.34), respectively, leads to two coupled equations for B and D

$$\begin{aligned} Be^{\lambda _{-}t_{1}}&=D-\frac{1}{\varepsilon \left( \lambda _{+}-\lambda _{-}\right) }, \end{aligned}$$
(17.37)
$$\begin{aligned} De^{\lambda _{-}t_{21}}&=\frac{1}{\varepsilon \left( \lambda _{+}-\lambda _{-}\right) }+B. \end{aligned}$$
(17.38)

By using (17.37), we eliminate D into Eq. (17.38) and find

$$\begin{aligned} B=\frac{1-e^{\lambda _{-}t_{21}}}{\varepsilon \left( \lambda _{+}-\lambda _{-}\right) \left[ e^{\lambda _{-}t_{2}}-1\right] }. \end{aligned}$$
(17.39)

Introducing then B given by (17.39) into Eq. (17.37), we obtain D as

$$\begin{aligned} D=\frac{e^{\lambda _{-}t_{1}}-1}{\varepsilon \left( \lambda _{+}-\lambda _{-}\right) \left[ e^{\lambda _{-}t_{2}}-1\right] }. \end{aligned}$$
(17.40)

Inserting (17.37) into (17.35) and (17.38) into (17.36) provides two coupled equations for A and C given by

$$\begin{aligned} Ae^{\lambda _{+}t_{1}}&=C+\frac{1}{\varepsilon \left( \lambda _{+}-\lambda _{-}\right) }, \end{aligned}$$
(17.41)
$$\begin{aligned} Ce^{\lambda _{+}t_{21}}&=A-\frac{1}{\varepsilon \left( \lambda _{+}-\lambda _{-}\right) }. \end{aligned}$$
(17.42)

Using (17.41), we eliminate C in Eq. (17.42) and find

$$\begin{aligned} A=\frac{e^{\lambda _{+}t_{21}}-1}{\varepsilon \left( \lambda _{+}-\lambda _{-}\right) \left[ e^{\lambda _{+}t_{2}}-1\right] }. \end{aligned}$$
(17.43)

Finally, introducing A given by (17.43) into Eq. (17.41) provides C as

$$\begin{aligned} C=\frac{1-e^{\lambda _{+}t_{1}}}{\varepsilon \left( \lambda _{+}-\lambda _{-}\right) \left[ e^{\lambda _{+}t_{2}}-1\right] }. \end{aligned}$$
(17.44)

From Fig. 17.4b, we note that x increases at time \(t=0\) when \(x(t-\tau )=a\). At time \(t=\delta \), it is the turn of x to equal a. From Fig. 17.4c, we note that \(t=t_{1}\) and \(t=t_{1}+\delta \) mark the times where \( x(t-\tau )\) and then x are equal to a. Using (17.9) with \(x(\delta )=a\) and (17.13) with \(x(t_{1}+\delta )=a\), we obtain

$$\begin{aligned} Ae^{\lambda _{+}\delta }+Be^{\lambda _{-}\delta }&=a, \end{aligned}$$
(17.45)
$$\begin{aligned} Ce^{\lambda _{+}\delta }+De^{\lambda _{-}\delta }&=a. \end{aligned}$$
(17.46)

Equations (17.31)–(17.46) with

$$\begin{aligned} t_{2}=T_{n}, \end{aligned}$$
(17.47)

defined by (17.6), are six equations for seven unknowns, namely A, B, C, D, \(t_{1}\), and \(\delta \). We introduce the expressions of A, B, C, and D into Eqs. (17.45) and (17.46), and find

$$\begin{aligned} a\varepsilon \left( \lambda _{+}-\lambda _{-}\right)&=\frac{1-e^{\lambda _{+}t_{21}}}{1-e^{\lambda _{+}t_{2}}}e^{\lambda _{+}\delta }+\frac{ e^{\lambda _{-}t_{21}}-1}{1-e^{\lambda _{-}t_{2}}}e^{\lambda _{-}\delta }, \end{aligned}$$
(17.48)
$$\begin{aligned} a\varepsilon \left( \lambda _{+}-\lambda _{-}\right)&=\frac{e^{\lambda _{+}t_{1}}-1}{1-e^{\lambda _{+}t_{2}}}e^{\lambda _{+}\delta }+\frac{ 1-e^{\lambda _{-}t_{1}}}{1-e^{\lambda _{-}t_{2}}}e^{\lambda _{-}\delta }. \end{aligned}$$
(17.49)

Substracting side by side, we eliminate \(a\varepsilon \left( \lambda _{+}-\lambda _{-}\right) \). Multiplying then by \(e^{-\lambda _{+}\delta }\), we have

$$\begin{aligned} 0=\frac{2-e^{\lambda _{+}t_{21}}-e^{\lambda _{+}t_{1}}}{1-e^{\lambda _{+}t_{2}}}+\left( \frac{e^{\lambda _{-}t_{21}}-2+e^{\lambda _{-}t_{1}}}{ 1-e^{\lambda _{-}t_{2}}}\right) e^{\left( \lambda _{-}-\lambda _{+}\right) \delta }. \end{aligned}$$
(17.50)

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Weicker, L., Keuninckx, L., Friart, G., Danckaert, J., Erneux, T. (2016). Multirhythmicity for a Time-Delayed FitzHugh-Nagumo System with Threshold Nonlinearity. In: Schöll, E., Klapp, S., Hövel, P. (eds) Control of Self-Organizing Nonlinear Systems. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-28028-8_17

Download citation

Publish with us

Policies and ethics