Skip to main content

On the Moments of Firing Numbers in Diffusion Neuronal Models with Refractoriness

  • Conference paper
Mechanisms, Symbols, and Models Underlying Cognition (IWINAC 2005)

Abstract

For diffusion neuronal models, the statistical features of the random variable modeling the number of neuronal firings are analyzed by including the additional assumption of the existence of random refractoriness. For long times, the asymptotic behaviors of the mean and variance of the number of firings released by the neuron are determined. Finally, simple asymptotic expressions are obtained under the assumption of exponentially distributed firing times.

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 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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Buonocore, A., Giorno, V., Nobile, A.G., Ricciardi, L.M.: Towards modeling refractoriness for single neuron’s activity. In: Trappl, R. (ed.) Cybernetics and Systems 2002, vol. 1, pp. 319–324. Austrian Society for Cybernetics Studies, Vienna (2002)

    Google Scholar 

  2. Buonocore, A., Giorno, V., Nobile, A.G., Ricciardi, L.M.: A neuronal modeling paradigm in the presence of refractoriness. BioSystems 67, 35–43 (2002)

    Article  Google Scholar 

  3. Esposito, G., Giorno, V., Nobile, A.G., Ricciardi, L.M., Valerio, C.: Interspike analysis for a single neuron’s activity in presence of refractoriness. In: Trappl, R. (ed.) Cybernetics and Systems. Austrian Society for Cybernetics Studies, Vienna, vol. 1, pp. 199–204 (2004)

    Google Scholar 

  4. Feller, W.: On probability problems in the theory of counters. In: Studies and Essays, A Volume for the Anniversary of Courant, pp. 105–115. Interscience Publishers, Inc., New York (1948)

    Google Scholar 

  5. Feller, W.: The parabolic differential equations and the associated semi–groups of transformations. Ann. Math. 55, 468–518 (1952)

    Article  MathSciNet  Google Scholar 

  6. Giorno, V., Lánský, P., Nobile, A.G., Ricciardi, L.M.: Diffusion approximation and first–passage–time problem for a model neuron. III. A birth–and–death process approach. Biol. Cybern. 58, 387–404 (1988)

    MATH  Google Scholar 

  7. Gradshteyn, I.S., Ryzhik, I.M.: Tables of Integrals, Series and Products. Academic Press, New York (1980)

    Google Scholar 

  8. Giorno, V., Nobile, A.G., Ricciardi, L.M.: On the asymptotic behavior of first– passage–time densities for one–dimensional diffusion processes and varying boundaries. Adv. Appl. Prob. 22, 883–914 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  9. Giorno, V., Nobile, A.G., Ricciardi, L.M.: Instantaneous return process and neuronal firings. In: Trappl, R. (ed.) Cybernetics and Systems Research 1992, pp. 829–836. World Scientific, Singapore (1992)

    Google Scholar 

  10. Giorno, V., Nobile, A.G., Ricciardi, L.M.: On asymptotic behaviors of stochastic models for single neuron’s activity. In: Trappl, R. (ed.) Cybernetics and System 1996. Austrian Society for Cybernetic Studies, pp. 524–529 (1996)

    Google Scholar 

  11. Ricciardi, L.M., Di Crescenzo, A., Giorno, V., Nobile, A.G.: On the instantaneous return process for neuronal diffusion models. In: Marinaro, M., Scarpetta, G. (eds.) Structure: from Physics to General Systems, pp. 78–94. World Scientific, Singapore (1992)

    Google Scholar 

  12. Ricciardi, L.M., Di Crescenzo, A., Giorno, V., Nobile, A.G.: An outline of theoretical and algorithmic approaches to first passage time problems with applications to biological modeling. Math. Japonica. 50(2), 247–322 (1999)

    MATH  Google Scholar 

  13. Ricciardi, L.M., Esposito, G., Giorno, V., Valerio, C.: Modeling Neuronal Firing in the Presence of Refractoriness. In: Mira, J., Álvarez, J.R. (eds.) IWANN 2003. LNCS, vol. 2686, pp. 1–8. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  14. Siegert, A.J.F.: On the first passage time probability problem. Phys. Rev. 81, 617–623 (1951)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Giorno, V., Nobile, A.G., Ricciardi, L.M. (2005). On the Moments of Firing Numbers in Diffusion Neuronal Models with Refractoriness. In: Mira, J., Álvarez, J.R. (eds) Mechanisms, Symbols, and Models Underlying Cognition. IWINAC 2005. Lecture Notes in Computer Science, vol 3561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499220_20

Download citation

  • DOI: https://doi.org/10.1007/11499220_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26298-5

  • Online ISBN: 978-3-540-31672-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics