[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Lookup Table Powered Neural Event-Driven Simulator

  • Conference paper
Computational Intelligence and Bioinspired Systems (IWANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3512))

Included in the following conference series:

Abstract

A novel method for efficiently simulating large scale realistic neural networks is described. Most information transmission in these networks is accomplished by the so called action potentials, events which are considerably sparse and well-localized in time. This facilitates a dramatic reduction of the computational load through the application of the event-driven simulation schemes. However, some complex neuronal models require the simulator to calculate large expressions, in order to update the neuronal state variables between these events. This requirement slows down these neural state updates, impeding the simulation of very active large neural populations in real-time. Moreover, neurons of some of these complex models produce firings (action potentials) some time after the arrival of the presynaptic potentials. The calculation of this delay involves the computation of expressions that sometimes are difficult to solve analytically. To deal with these problems, our method makes use of precalculated lookup tables for both, fast update of the neural variables and the prediction of the firing delays, allowing efficient simulation of large populations with detailed neural models.

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. Van Rullen, R., Gautrais, J., Delorme, A., Thorpe, S.: Face processing using one spike per neurone. BioSystems 48, 229–239 (1998)

    Article  Google Scholar 

  2. Philipona, D., Coenen, O.J.M.D.: Model of granular layer encoding in the cerebellum. Neurocomputing 58-60, 575–580 (2004)

    Article  Google Scholar 

  3. Bower, J.M., Beeman, B.: The book of GENESIS. Springer, New York (1998)

    Google Scholar 

  4. Delorme, A., Thorpe, S.: SpikeNET: An event-driven simulation package for modelling large networks of spiking neurons. Network. Computation in Neural Systems 14, 613–627 (2003)

    Article  Google Scholar 

  5. Watts, L.: Event-driven simulation of networks of spiking neurons. In: Cowan, J.D., Tesauro, G., Alspector, J. (eds.) Advances in neural information processing systems, San Mateo CA, vol. 6, pp. 934–967. Morgan Kaufmann, San Francisco (1994)

    Google Scholar 

  6. Graβmann, C., Anlauf, J.K.: Fast digital simulation of spiking neural networks and neuromorphic integration with SPIKELAB. International Journal of Neural Systems 9(5), 473–478 (1999)

    Article  Google Scholar 

  7. Mattia, M., Del Guidice, P.: Efficient event-driven simulation of large networks of spiking neurons and dynamical synapses. Neural Computation 12(10), 2305–2329 (2000)

    Article  Google Scholar 

  8. Makino, T.: A Discrete-Event Neural Network Simulator for General Neuron Models. Neural Comput & Applic. 11, 210–223 (2003)

    Article  MATH  Google Scholar 

  9. Reutimann, J., Guigliano, M., Fusi, S.: Event-driven simulation of spiking neurons with stochastic dynamics. Neural Computation 15, 811–830 (2003)

    Article  MATH  Google Scholar 

  10. Brette, R.: Event-driven simulation of integrate-and-fire neurons with exponential synaptic conductances. Submitted to Journal of Computational Neuroscience (2004)

    Google Scholar 

  11. Eckhorn, R., Bauer, R., Jordan, W., Brosh, M., Kruse, W., Munk, M., Reitböck, H.J.: Coherent oscillations: A mechanism of feature linking in the visual cortex? Biol. Cyber. 60, 121–130 (1988)

    Article  Google Scholar 

  12. Eckhorn, R., Reitböck, H.J., Arndt, M., Dicke, D.: Feature Linking via Synchronization among Distributed Assemblies: Simulations of Results from Cat Visual Cortex. Neural Computation 2, 293–307 (1990)

    Article  Google Scholar 

  13. Karlton, P.L., Fuller, S.H., Scroggs, R.E., Kaehler, E.B.: Performance of height-balanced trees. Information retrieval and language processing. Communications of ACM 19(1), 23–28 (1976)

    MATH  Google Scholar 

  14. Pugh, W.: Skip lists: A probabilistic alternative to balanced trees. Communications of the ACM 33(6), 668–676 (1990)

    Article  MathSciNet  Google Scholar 

  15. Aho, A.V., Hopcroft, J.E., Ullman, J.D.: The design and analysis of computer algorithms. Addison-Wesley, Reading (1974)

    MATH  Google Scholar 

  16. Chowdhury, R.A., Kaykobad, M.: Sorting using heap structure. In: Proceedings of Int. Conf. on Comp. and Inf. Tech., Dhaka, Bangladesh, pp. 26–30 (2001)

    Google Scholar 

  17. Cormen, T.H., Lierson, C.E., Rivest, R.L.: Introduction to algorithms, pp. 140–152. MIT Cambridge press, Cambridge (1990)

    MATH  Google Scholar 

  18. Gerstner, W., Kistler, W.: Spiking neuron models: Single neurons, populations, plasticity. Cambridge University, Cambridge (2002)

    MATH  Google Scholar 

  19. Ros, E., Pelayo, F.J., Martín-Smith, P., Palomar, D., Prieto, A.: Competitive and Temporal Inhibition Structures with Spiking Neurons. Neural Processing Letters 11(3), 197–208 (2000)

    Article  Google Scholar 

  20. Chez, C.: The Cerebellum. In: Kandel, E., Schwartz, J.H., Jessel (eds.) Principles of Neural Science, 3rd edn., pp. 626–645 (1991)

    Google Scholar 

  21. Ros, E., Carrillo, R., Ortigosa, E.M., Barbour, B., Agís, R.: Event-driven Simulation Scheme for Spiking Neural Models based on Characterization Look-up Tables. Submitted to Neural Computation in 2004

    Google Scholar 

  22. Hines, M.L., Carnevale, N.T.: The NEURON simulation environment. Neural Computation 9, 1179–1209 (1997)

    Article  Google Scholar 

  23. Delorme, A., Gautrais, J., van Rullen, R., Thorpe, S.: SpikeNET: A simulator for modelling large networks of integrate and fire neurons. In: Bower, J.M. (ed.) Computational Neuroscience: Trends in research 1999, Neurocomputing, vol. 26-27, pp. 989–996 (1999)

    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

Carrillo, R.R., Ros, E., Ortigosa, E.M., Barbour, B., Agís, R. (2005). Lookup Table Powered Neural Event-Driven Simulator. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_22

Download citation

  • DOI: https://doi.org/10.1007/11494669_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26208-4

  • Online ISBN: 978-3-540-32106-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics