Neural Processing Letters

, Volume 6, Issue 3, pp 91–98 | Cite as

A Neural Network Model of Caenorhabditis Elegans: The Circuit of Touch Sensitivity

  • Angelo Cangelosi
  • Domenico Parisi
Article

Abstract

The paper presents a neural network model of the touch sensitivity circuit of the nematode Caenorhabditis elegans. We describe a serie of simulations in which neural networks are trained, using a genetic algorithm, to reproduce the habituation of the nematode's touch sensitive behavior. A lesion study of the network allows to make a direct comparison between the fine functioning of the model and the data collected in real organisms. The model accords well with the known neurobiological data and it suggests some hypotheses about the functioning of the neural circuit and of single neurons.

computational neuroscience C. elegans genetic algorithm lesion study 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    T.J. Sejnowski, C. Koch and P.S. Churchland, “P.S. Computational neuroscience”, Science, Vol. 241, pp. 1299–1306, 1988.Google Scholar
  2. 2.
    S.R. Lochery and T.J. Sejnowsky, “Distributed processing of sensory information in the Leech. III. A dynamical neural network model of the local bending reflex”, Journal of Neuroscience, Vol. 12, pp. 3877–3895, 1992.Google Scholar
  3. 3.
    M. Chalfie, J.E. Sulston, J.C. White, E. Southgate, J.N. Thomson and S. Brenner, “The neural circuit for touch sensitivity in Caenorhabditis elegans”, Journal of Neuroscience, Vol. 5, pp. 959–964, 1985.Google Scholar
  4. 4.
    S.R. Wicks and C.H. Rankin, “Integration of mechanosensory stimuli in Caenorhabditis elegans”, Journal of Neuroscience, Vol. 15, pp. 2434–2444, 1995.Google Scholar
  5. 5.
    W.B. Wood (ed), The Nematode Caenorhabditis elegans, Cold Spring Harbor Laboratory, 1988.Google Scholar
  6. 6.
    J.P. Walrond and A.O. Stretton, “Reciprocal Inhibition in the motor nervous system of the nematode Ascaris: direct control of ventral inhibitory motoneurons by dorsal excitatory motoneurons”, Journal of Neuroscience, Vol. 5, pp. 9–15, 1985.Google Scholar
  7. 7.
    J.J Holland, Adaptation in Natural and Artificial Systems, Ann Arbor, Michigan: University of Michigan Press, 1975.Google Scholar
  8. 8.
    C.H. Rankin, C.D. Beck and C.M. Chiba, “Caenorhabditis elegans: a new model system for the study of learning and memory”, Behavioral Brain Research, Vol. 37, pp. 89–92, 1990.Google Scholar
  9. 9.
    J.G. White, D.G. Albertson and M.A. Anness, “Connectivity changes in a class of motoneurone during the development of a Nematode”, Nature, Vol. 271, pp. 764–766, 1978.Google Scholar
  10. 10.
    P.M. Groves and R.F. Thompson, “Habituation: a dual process theory”, Psychological Review, Vol. 77, pp. 419–450, 1970.Google Scholar

Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Angelo Cangelosi
    • 1
  • Domenico Parisi
    • 1
    • 2
  1. 1.Department of Neural Systems and Artificial LifeInstitute of PsychologyRomeItaly
  2. 2.Center for Neural and Adaptive SystemsUniversity of Plymouth, Drake CircusPlymouth

Personalised recommendations