Skip to main content

Finding Periodic Orbits in the Hindmarsh-Rose Neuron Model

  • Conference paper
  • First Online:

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 54))

Abstract

In this work we apply a modified search method based on the stability transformation method, combined with the Newton method, to the classical neuronal model proposed by Hindmarsh and Rose in 1984. We have selected two values of parameter b corresponding to chaotic-bursting behavior (b = 2.69 and b = 3.05). For these values we have studied the changes of the chaotic attractors by obtaining the complete set of unstable periodic orbits up to multiplicity four. For b = 2.69 we have found 1, 1, 2 and 3 POs of multiplicity one to four, respectively, and for b = 3.05 we have found 1, 1, 0, 1 POs of multiplicity one to four, and thus giving a different chaotic attractor.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   109.99
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

Learn about institutional subscriptions

References

  1. Abad, A., Barrio, R., Dena, A.: Computing periodic orbits with arbitrary precision. Phys. Rev. E 84, 6 (2011)

    Article  Google Scholar 

  2. Abad, A., Barrio, R., Blesa, F., Rodríguez, M.: Algorithm 924: TIDES, a Taylor series integrator for differential equations. ACM Trans. Math. Softw. 39, 5:1–5:28 (2012). http://gme.unizar.es/software/tides

    Google Scholar 

  3. Abad, A., Barrio, R., Martínez, M.A., Serrano, S.: Finding Periodic Orbits in Time Continuous Dynamical Systems (in preparation)

    Google Scholar 

  4. Barrio, R., Shilnikov, A.: Parameter-sweeping techniques for temporal dynamics of neuronal systems: case study of Hindmarsh-Rose model. J. Math. Neurosci. 1, 6 (2011)

    Article  MathSciNet  Google Scholar 

  5. Davidchack, R.L., Lai, Y.C.: Efficient algorithm for detecting unstable periodic orbits in chaotic systems. Phys. Rev. E 60, 6172 (1999)

    Article  Google Scholar 

  6. Hindmarsh, J.L., Rose, R.M.: A model of the nerve impulse using three coupled first-order differential equations. Proc. R. Soc. Lond. B221, 87–102 (1984)

    Article  Google Scholar 

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

    Google Scholar 

  8. Pingel, D., Schemelcher, P., Diakonos, F.K.: Detecting unstable periodic orbits in chaotic continuous-time dynamical systems. Phys. Rev. E 64, 026214 (2001)

    Article  Google Scholar 

  9. Schemelcher, P., Diakonos, F.K.: Detecting unstable periodic orbits of chaotic dynamical systems. Phys. Rev. Lett. 78, 4733 (1997)

    Article  Google Scholar 

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

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by Spanish Research project AYA2008-05572 (to M.A.M.) and by the Spanish Research project MTM2012-31883 (to R.B. and S.S.). We acknowledge Prof. Andrey Shilnikov for valuable comments and fruitful discussions about neuron models.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Angeles Martínez .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Martínez, M.A., Barrio, R., Serrano, S. (2013). Finding Periodic Orbits in the Hindmarsh-Rose Neuron Model. In: Ibáñez, S., Pérez del Río, J., Pumariño, A., Rodríguez, J. (eds) Progress and Challenges in Dynamical Systems. Springer Proceedings in Mathematics & Statistics, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38830-9_18

Download citation

Publish with us

Policies and ethics