Advertisement

Self-organised Criticality in a Model of the Rat Somatosensory Cortex

  • Grzegorz M. Wojcik
  • Wieslaw A. Kaminski
  • Piotr Matejanka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4671)

Abstract

Large Hodgkin-Huxley (HH) neural networks were examined and the structures discussed in this article simulated a part of the rat somatosensory cortex. We used a modular architecture of the network divided into layers and sub-regions. Because of a high degree of complexity effective parallelisation of algorithms was required. The results of parallel simulations were presented. An occurrence of the self-organised criticality (SOC) was demonstrated. Most notably, in large biological neural networks consisting of artificial HH neurons, the SOC was shown to manifest itself in the frequency of its appearance as a function of the size of spike potential avalanches generated within such nets. These two parameters followed the power law characteristic of other systems exhibiting the SOC behaviour.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bak, P.: How nature works: The Science of Self-Organised Criticality. Copernicus Press, New York (1996)Google Scholar
  2. 2.
    Bower, J.M., Beeman, D.: The Book of GENESIS - Exploring Realistic Neural Models with the GEneral NEural SImulation System. Telos, New York (1995)Google Scholar
  3. 3.
    Jensen, H.J.: Self Organizing Criticality. Cambridge University Press, Cambridge (1998)Google Scholar
  4. 4.
    Aegerter, C.M., Gnther, R., Wijngaarden, R.J.: Avalanche dynamics, surface roughening, and self-organized criticality: Experiments on a three-dimensional pile of rice Phys. Rev. E 67 (2003) 051306Google Scholar
  5. 5.
    Bak, P., Christensen, K., Danon, L., Scanlon, T.: Unified Scaling Law for Earthquakes Phys. Rev. Lett. 88 (2002) 178501Google Scholar
  6. 6.
    Bak, P., Tang, C., Wisenfeld, K.: Self-organized criticality: An explanation of the 1/f noise Phys. Rev. Lett. 59, 381–384 (1987)CrossRefGoogle Scholar
  7. 7.
    Garcia-Lazaro, J.A., Ho, S.S.M., Nair, A., Schnupp, J.W.H: Adaptation to Stimulus in Rat Somatosensory Cortex. FENS Abstr. 3, A109.4 (2006)Google Scholar
  8. 8.
    Lubeck, S.: Crossover phenomenon in self-organized critical sandpile models Phys. Rev. E 62, 6149–6154 (2000)Google Scholar
  9. 9.
    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
  10. 10.
    Paczuski, M., Bassler, K.E.: Theoretical results for sandpile models of self-organized criticality with multiple topplings Phys. Rev. E. E 62, 5347–5352 (2000)MathSciNetGoogle Scholar
  11. 11.
    Pastor-Satorras, R., Vespignani, A.: Corrections to scaling in the forest-fire model Phys. Rev. E 61, 4854–4859 (2000)Google Scholar
  12. 12.
    Yang, X., Du, S., Ma, J.: Do Earthquakes Exhibit Self-Organized Criticality? Phys. Rev. Lett. 92 (2004) 228501Google Scholar
  13. 13.
    CLUSTERIX - The National Cluster of Linux Systems, http://www.clusterix.pcz.pl
  14. 14.
  15. 15.
  16. 16.
    A definition of an SOC, http://www.wikipedia.org

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Grzegorz M. Wojcik
    • 1
  • Wieslaw A. Kaminski
    • 1
  • Piotr Matejanka
    • 2
  1. 1.Institute of Computer Science, Maria Curie-Sklodowska University, pl. Marii Curie-Sklodowskiej 5, 20-031-LublinPoland
  2. 2.Motorola Polska Electronics, ul. Wadowicka 6, 30-415 KrakowPoland

Personalised recommendations