Skip to main content

A unified model for the simulation of artificial and biology-oriented neural networks

  • Artificial Neural Nets Simulation and Implementation
  • Conference paper
  • First Online:
Engineering Applications of Bio-Inspired Artificial Neural Networks (IWANN 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1607))

Included in the following conference series:

Abstract

A unified model for the simulation of artificial and biologyoriented neural networks is presented. It supports all rate-coded and also many pulse-coded neural network models. The focus of the paper is on the special requirements for the simulation of neural networks built from neurons modelled by a single compartment. The derived unified neural network model represents a basis for the design of a universal neurosimulator. Several extensions of the neural specification language EpsiloNN to incorporate the new model are explained.

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. Bower, J., and Beeman, D. The book of GENESIS: exploring realistic neural models with the GEneral NEural SImulation System. Springer, New York, 1995.

    MATH  Google Scholar 

  2. Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M., and Reitboeck, H. Coherent Oscillations: A mechanism of feature linking in the visual cortex? Biological Cybernetics 60 (1988), 121–130.

    Article  Google Scholar 

  3. Gerstner, W. Spiking Neurons. In Pulsed Neural Networks, W. Maas and C. Bishop, Eds. MIT Press, 1998, ch. 1, pp. 3–54.

    Google Scholar 

  4. Hartmann, G., Frank, G., Schäfer, M., and Wolff, C. Spike 128K-An Accelerator for Dynamic Simulation of Large Pulse-Coded Networks. In Proceedings MicroNeuro'97 (1997), H. Klar, A. Koenig, and U. Ramacher, Eds., pp. 130–139.

    Google Scholar 

  5. Hecht-Nielsen, R. Neurocomputing. Addison-Wesley, 1990.

    Google Scholar 

  6. Hines, M., and Carnevale, N. The NEURON Simulation Environment. Neural Computation 9 (1997), 1179–1209.

    Article  Google Scholar 

  7. Jahnke, A., Roth, U., and Schönauer, T. Digital Simulation of Spiking Neural Networks. In Pulsed Neural Networks, W. Maas and C. Bishop, Eds. MIT Press, 1998, ch. 9.

    Google Scholar 

  8. Kock, G., and Šerbedžija, N. Artificial Neural Networks: From compact descriptions to C++. In Proceedings of the International Conference on Artificial Neural Networks ICANN'94 (1994), Springer, pp. 1372–1375.

    Google Scholar 

  9. NeuralWare, Inc., Pittsburgh(PA). NeuralWorks Reference Guide, 1995.

    Google Scholar 

  10. Sajda, P., and Finkel, L. NEXUS: A simulation environment for large-scale neural systems. SIMULATION 59, 6 (1992), 358–364.

    Google Scholar 

  11. Singer, W., and Gray, C. Visual feature integration and the temporal correlation hypotheses. Ann. Rev. Neuroscience 18 (1995), 555–586.

    Article  Google Scholar 

  12. Strey, A. EpsiloNN—A Specification Language for the Efficient Parallel Implementation of Neural Networks. In Biological and Artificial Computation: From Neuroscience to Technology, LNCS 1240 (Berlin, 1997), J. Mira, R. Moreno-Dìaz, and J. Cabestany, Eds., Springer, pp. 714–722.

    Google Scholar 

  13. Strey, A. EpsiloNN—A Tool for the Abstract Specification and Parallel Simulation of Neural Networks. Systems Analysis Modelling Simulation (SAMS), Gordon & Breach, 1999, in print.

    Google Scholar 

  14. Teeters, J. MDL: A system for fast simulation of layered neural networks. SIMULATION 56, 6 (June 1991), 369–379.

    Google Scholar 

  15. Walker, M., Wang, H., Kartamihardjo, S., and Roth, U. SimSPiNN—A Simulator for Spike-Processing Neural Networks. In Proceedings of the 15th IMACS World Congress on Scientific Computation, Modelling and Applied Mathematics (Berlin, 1997), A. Sydow, Ed., Wissenschaft & Technik Verlag.

    Google Scholar 

  16. Watts, L. Event-driven simulation of networks of spiking neurons. In Advances in Neural Information Processing Systems (1994), J. Cowan, G. Tesauro, and J. Alspector, Eds., vol. 6, Morgan Kaufmann Publishers, Inc., pp. 927–934.

    Google Scholar 

  17. Zell, A. et al. SNNS Stuttgart Neural Network Simulator, User Manual, Version 4.0. Report 6/95, University of Stuttgart, 1995.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

José Mira Juan V. Sánchez-Andrés

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Strey, A. (1999). A unified model for the simulation of artificial and biology-oriented neural networks. In: Mira, J., Sánchez-Andrés, J.V. (eds) Engineering Applications of Bio-Inspired Artificial Neural Networks. IWANN 1999. Lecture Notes in Computer Science, vol 1607. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0100466

Download citation

  • DOI: https://doi.org/10.1007/BFb0100466

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66068-2

  • Online ISBN: 978-3-540-48772-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics