Function of biological asymmetrical neural networks | SpringerLink
Skip to main content

Function of biological asymmetrical neural networks

  • Neural Networks for Perception
  • Conference paper
  • First Online:
Biological and Artificial Computation: From Neuroscience to Technology (IWANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1240))

Included in the following conference series:

Abstract

Nonlinearity is an important factor in the biological neural networks. The motion perception and learning in them have been studied on the simplest type of nonlinearity, multiplication. In this paper, asymmetrical neural networks with nonlinear function, are studied in the biological neural networks. Then, the nonlinear higher-order system is discussed in the neural networks. The second-order system in the nonlinear biological system is shown to play an important role in the movement detection. From the theoretical analysis, it is shown that the third-order one does not contribute to the detection and the fourth-order one becomes to the second-order in the movement detection function. Hassenstein and Reichardt network(1956) and Barlow and Levick network(1965) of movements are similar to the asymmetrical network developed here. To make clear the difference among these asymmetrical networks, we derive α-equation of movement, which shows the detection of movement. During the movement, we also can derive the movement equation, which implies the movement direction regardless of the parameter α.

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.

References

  1. Hassenstein, B. and Reichardt, W., Systemtheoretische Analyse der Zeit-, Reihenfolgen and Vorzeichenauswertung bei der Bewegungsperzeption des Russelkafers, Chlorophanus. Z. Naturf, 11b, pp.513–524, 1956.

    Google Scholar 

  2. Barlow, H.B. and Levick, R.W., The mechanism of directional selectivity in the rabbit's retina, J. physiol. 173: pp.377–407, 1965.

    Google Scholar 

  3. Victor J.D. and Shapley K.M., The Nonlinear Pathway of Y Ganglion Cells in the Cat Retina, J. Gen. Physiol., vol. 74, pp. 671–689, 1979.

    Google Scholar 

  4. Ishii, N., Motion detection by biological asymmetrical neural network. Proc. IJCNN. 3, Boltimore, MD. pp.390–395, 1992.

    Google Scholar 

  5. Ishii, N., Modified differentiation and nonlinear function in motion detection of neural network. Proc. Int. Fuzzy Logic & Neural Networks, 2, Iizuka, pp.867–870, 1992.

    Google Scholar 

  6. Ishii, N., Kernel Correlations of Movements in Neural Network, Proc. of International Conference on Artificial Neural Networks, Vol. II, pp. 110–113, 1994.

    Google Scholar 

  7. Ishii, N. and Naka K.-L, Movement and Memory Function in Biological Neural Networks, Proc. Int. IEEE Symp. on Intelligence in Neural and Biological Systems, pp. 6–11, 1995.

    Google Scholar 

  8. Korenberg, M.J., Sakai, H.M. and Naka, K.-L, Dissection of the neuron network in the catfish inner retina. J. Neurophysiol. 61: pp.1110–1120, 1989.

    Google Scholar 

  9. Liaw, J.S. and Arbib, M.A., A biologically inspired neural network model for 3-D motion detection. Proc. IJCNN. 1:, Seattle, WA. pp 661–665, 1991.

    Google Scholar 

  10. Marmarelis, P.Z. and Marmarelis, V.Z., Analysis of physiological system: The white noise approach. New York: Plenum Press, 1978.

    Google Scholar 

  11. Naka, K.-L, Sakai, H.M. and Ishii, N., Generation and transformation of second order nonlinearity in catfish retina, Annals of Biomedical Engineering. 16: pp. 53–64, 1988.

    Google Scholar 

  12. Reichardt, W., Autocorrelation, a princeple for the evaluation of sensory information by the central nervous system. Rosenblith, WA., Wiley, New York, 1961.

    Google Scholar 

  13. Sakai, H.M. and Naka, K.-L, Signal transmission in the catfish retina. J. Neurophysiol. 58: pp.1329–1350, 1987.

    Google Scholar 

  14. Koch, C. and Poggio, T., Multiplying with Synapses and neurons, in Single Neuron Computation. New York: Academic Press, 1992

    Google Scholar 

  15. Sakuranaga, M and Naka, K.-L, Signal Signal transmission in the catfish retina. III. Transmission to type-C cell. J.Neurophysiol. 58: pp.411–428, 1987

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

José Mira Roberto Moreno-Díaz Joan Cabestany

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ishii, N., Naka, Ki. (1997). Function of biological asymmetrical neural networks. In: Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032571

Download citation

  • DOI: https://doi.org/10.1007/BFb0032571

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63047-0

  • Online ISBN: 978-3-540-69074-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics