Nothing Special   »   [go: up one dir, main page]

Skip to main content

Modeling retinal high and low contrast sensitivity filters

  • Neuroscience
  • Conference paper
  • First Online:
From Natural to Artificial Neural Computation (IWANN 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 930))

Included in the following conference series:

Abstract

In this paper two types of ganglion cells in the visual system of mammals (monkey) are modeled. A high contrast sensitive type, the so called M-cells, which project to the two magno-cellular layers of the lateral geniculate nucleus (LGN) and a low sensitive type, the P-cells, which project to the four parvo-cellular layers of the LGN. The results will be compared with the ganglion cells as described by Kuffler.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. S. W. Kuffler. Discharge patterns and functional organization of mammalian retina. Journal of Neurophysiology, 16:37–68, 1953.

    PubMed  Google Scholar 

  2. David H. Hubel. Eye, Brain and Vision. Scientific American Library, New York, 1988.

    Google Scholar 

  3. E. Kaplan and R. M. Shapley. The primate retina contains two types of ganglion cells, with high and low contrast sensitivity. Proc. Natl. Acad. Sci. U.S.A., 83:2755–2757, April 1986.

    PubMed  Google Scholar 

  4. Robert Shapley and V. Hugh Peny. Cat and monkey retinal ganglion cells and their visual functional roles. Trends in Neuroscience (TINS), 9:229–235, May 1986.

    Google Scholar 

  5. Margaret Livingstone and David Hubel. Segregation of form, color, movement, and depth: Anatomy, physiology, and perception. Science, 240:740–749,1988.

    PubMed  Google Scholar 

  6. John G. Nicholls, A. Robert Martin, and Bruce G. Wallace. From Neuron to Brain-A Cellular Molecular Approach to the Function of the Nervous System. Sinauer Associates, Inc., third edition, 1992.

    Google Scholar 

  7. T. Lourens. Building a biological filter, submitted to ESANN '95, 1995.

    Google Scholar 

  8. N. Petkov, P. Kruizinga, and T. Lourens. Biologically motivated approach to face recognition. In J. Mira, J. Cabestany, and A. Prieto, editors, New Trends in Neural Computation, Proceedings of the International Workshop on Artificial Neural Networks, IWANN '93, volume 686 of Lecture Notes in Computer Science, pages 68–77. Springer-Verlag Berlin Heidelberg, Sitges, Spain, June 9–11 1993.

    Google Scholar 

  9. N. Petkov and T. Lourens. Human visual systems simulations — an application to face recognition. In H. Dedieu, editor, Circuit Theory and Design 93, Proceedings of the 11 th Conference on Circuit Theory and Design, pages 821–826, Davos, Switzerland, Aug. 30–Sept. 3 1993. Elsevier Science Publishers B.V. Amsterdam.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

José Mira Francisco Sandoval

Rights and permissions

Reprints and permissions

Copyright information

© 1995 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lourens, T. (1995). Modeling retinal high and low contrast sensitivity filters. In: Mira, J., Sandoval, F. (eds) From Natural to Artificial Neural Computation. IWANN 1995. Lecture Notes in Computer Science, vol 930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59497-3_157

Download citation

  • DOI: https://doi.org/10.1007/3-540-59497-3_157

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-59497-0

  • Online ISBN: 978-3-540-49288-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics