Skip to main content

Contour Integration and Synchronization in Neuronal Networks of the Visual Cortex

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 5164)

Abstract

The visual perception of contours by the brain is selective. When embedded within a noisy background, closed contours are detected faster, and with higher certainty, than open contours. We investigate this phenomenon theoretically with the paradigmatic excitable FitzHugh-Nagumo model, by considering a set of locally coupled oscillators subject to local uncorrelated noise. Noise is needed to overcome the excitation threshold and evoke spikes. We model one-dimensional structures and consider the synchronization throughout them as a mechanism for contour perception, for various system sizes and local noise intensities. The model with a closed ring structure shows a significantly higher synchronization than the one with the open structure. Interestingly, the effect is most pronounced for intermediate system sizes and noise intensities.

Keywords

  • System Size
  • Noise Intensity
  • Stochastic Resonance
  • Open Chain
  • Closed Contour

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-540-87559-8_73
  • Chapter length: 10 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   139.00
Price excludes VAT (USA)
  • ISBN: 978-3-540-87559-8
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Singer, W.: Neuronal synchrony: A versatile code for the definition of relations? Neuron 24(1), 49–65 (1999)

    CrossRef  Google Scholar 

  2. Gray, C.M., König, P., Engel, A.K., Singer, W.: Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338, 334–337 (1989)

    CrossRef  Google Scholar 

  3. Castelo-Branco, M., Goebel, R., Neuenschwander, S., Singer, W.: Neural synchrony correlates with surface segregation rules. Nature 405, 685–689 (2000)

    CrossRef  Google Scholar 

  4. Sarpeshkar, R.: Analog versus digital: Extrapolating from electronics to neurobiology. Neural Comput. 10(7), 1601–1638 (1998)

    CrossRef  Google Scholar 

  5. Mori, T., Kai, S.: Noise-induced entrainment and stochastic resonance in human brain waves. Phys. Rev. Lett. 88, 218101 (2002)

    CrossRef  Google Scholar 

  6. Lee, S., Neiman, A., Kim, S.: Coherence resonance in a hodgkin-huxley neuron. Phys. Rev. E 57, 3292 (1998)

    CrossRef  Google Scholar 

  7. Pikovsky, A., Kurths, J.: Coherence resonance in a noise-driven excitable system. Phys. Rev. Lett. 78, 775 (1997)

    MATH  CrossRef  MathSciNet  Google Scholar 

  8. Lindner, B., Schimansky-Geier, L., Longtin, A.: Maximizing spike train coherence or incoherence in the leaky integrate-and-fire model. Phys. Rev. E 66, 31916 (2002)

    CrossRef  MathSciNet  Google Scholar 

  9. Longtin, A.: Autonomous stochastic resonance in bursting neurons. Phys. Rev. E 55, 868 (1997)

    CrossRef  Google Scholar 

  10. Palenzuela, C., Toral, R., Mirasso, C., Calvo, O., Gunton, J.: Coherence resonance in chaotic systems. Europhys. Lett. 56(3), 347–353 (2001)

    CrossRef  Google Scholar 

  11. Ganopolski, A., Rahmstorf, S.: Abrupt glacial climate changes due to stochastic resonance. Phys. Rev. Lett. 88, 038501 (2002)

    CrossRef  Google Scholar 

  12. Dubbeldam, J.L.A., Krauskopf, B., Lenstra, D.: Excitability and coherence resonance in lasers with saturable absorber. Phys. Rev. E 60, 6580–6588 (1999)

    CrossRef  Google Scholar 

  13. Buldú, J.M., García-Ojalvo, J., Mirasso, C.R., Torrent, M.C., Sancho, J.M.: Effect of external noise correlation in optical coherence resonance. Phys. Rev. E 64, 051109 (2001)

    CrossRef  Google Scholar 

  14. Hu, B., Zhou, C.: Phase synchronization in coupled nonidentical excitable systems and array-enhanced coherence resonance. Phys. Rev. E 61(2), R1001–R1004 (2000)

    CrossRef  Google Scholar 

  15. Keener, J.P., Sneyd, J.: Mathematical Physiology. Springer, New York (1998)

    MATH  Google Scholar 

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

    CrossRef  Google Scholar 

  17. Nagumo, J., Arimoto, S., Yoshitzawa, S.: An active pulse transmission line simulating nerve axon. Proc. IRE 50, 2061 (1962)

    CrossRef  Google Scholar 

  18. Mikhailov, A.S.: Foundations of Synergetics, 2nd edn. Springer, Berlin (1994)

    MATH  Google Scholar 

  19. García-Ojalvo, J., Elowitz, M.B., Strogatz, S.H.: Modeling a synthetic multicellular clock: Repressilators coupled by quorum sensing. Proc. Natl. Acad. Sci. U.S.A 101(30), 10955–10960 (2004)

    MATH  CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ullner, E., Vicente, R., Pipa, G., García-Ojalvo, J. (2008). Contour Integration and Synchronization in Neuronal Networks of the Visual Cortex. In: Kůrková, V., Neruda, R., Koutník, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87559-8_73

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-87559-8_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87558-1

  • Online ISBN: 978-3-540-87559-8

  • eBook Packages: Computer ScienceComputer Science (R0)