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SpikeStream: A Fast and Flexible Simulator of Spiking Neural Networks

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Artificial Neural Networks – ICANN 2007 (ICANN 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4668))

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Abstract

SpikeStream is a new simulator of biologically structured spiking neural networks that can be used to edit, display and simulate up to 100,000 neurons. This simulator uses a combination of event-based and synchronous simulation and stores most of its information in databases, which makes it easy to run simulations across an arbitrary number of machines. A comprehensive graphical interface is included and SpikeStream can send and receive spikes to and from real and virtual robots across a network. The architecture is highly modular, and so other researchers can use its graphical editing facilities to set up their own simulation networks or apply genetic algorithms to the SpikeStream databases. SpikeStream is available for free download under the terms of the GPL.

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References

  1. Ageia PhysX, http://www.ageia.com/developers/api.html

  2. Amygdala simulator, http://amygdala.sourceforge.net/

  3. Brader, J.M., Senn, W., Fusi, S.: Learning real world stimuli in a neural network with spike-driven synaptic dynamics. Neural Computation (submitted, 2006)

    Google Scholar 

  4. Brette, R., Rudolph, M., Carnevale, T., Hines, M., Beeman, D., Bower, J.M., Diesmann, M., Morrison, A., Goodman, P.H., Harris Jr., F.C., Zirpe, M., Natschlaeger, T., Pecevski, D., Ermentrout, B., Djurfeldt, M., Lansner, A., Rochel, O., Vieville, T., Muller, E., Davison, A.P., El Boustani, S., Destexhe, A.: Simulation of networks of spiking neurons: A review of tools and strategies. J. Comp. Neurosci (in press)

    Google Scholar 

  5. CAVIAR project, http://www.imse.cnm.es/caviar/

  6. Dehaene, S., Changeux, J.P.: Ongoing Spontaneous Activity Controls Access to Consciousness: A Neuronal Model for Inattentional Blindness. Public Library of Science Biology 3(5), 141 (2005)

    Google Scholar 

  7. Delorme, A., Thorpe, S.J.: SpikeNET: An Event-driven Simulation Package for Modeling Large Networks of Spiking Neurons. Network: Computational in Neural Systems 14, 613–627 (2003)

    Article  Google Scholar 

  8. Diesmann, M., Gewaltig, M.-O.: NEST: An Environment for Neural Systems Simulations. In: Macho, V. (ed.) Forschung und wissenschaftliches Rechnen, Heinz-Billing-Preis, GWDG-Bericht (2001)

    Google Scholar 

  9. Gamez, D., Newcombe, R., Holland, O., Knight, R.: Two Simulation Tools for Biologically Inspired Virtual Robotics. In: Proceedings of the IEEE 5th Chapter Conference on Advances in Cybernetic Systems, Sheffield, pp. 85–90. IEEE Computer Society Press, Los Alamitos (2006)

    Google Scholar 

  10. GENESIS simulator, http://www.genesis-sim.org/GENESIS/

  11. Gerstner, W., Kistler, W.: Spiking Neuron Models. Cambridge University Press, Cambridge (2002)

    MATH  Google Scholar 

  12. Krichmar, J.L., Seth, A.K., Nitz, D.A., Fleischer, J.G., Edelman, G.M.: Spatial navigation and causal analysis in a brain-based device modeling cortical-hippocampal interactions. Neuroinformatics 3, 197–221 (2005)

    Article  Google Scholar 

  13. Marian, I.: A biologically inspired computational model of motor control development. MSc Thesis, Department of Computer Science, University College Dublin, Ireland (2003)

    Google Scholar 

  14. Mvaspike simulator, http://www-sop.inria.fr/odyssee/softwares/mvaspike/

  15. NCS simulator, http://brain.cse.unr.edu/ncsDocs/

  16. NEURON simulator, http://www.neuron.yale.edu/neuron/

  17. Shanahan, M.P.: A Cognitive Architecture that Combines Internal Simulation with a Global Workspace. Consciousness and Cognition 15, 433–449 (2006)

    Article  Google Scholar 

  18. Spiking Neural Simulator, http://www.cs.stir.ac.uk/~lss/spikes/snn/index.html

  19. Topographica Neural Simulator, http://topographica.org/Home/index.html

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Essex, Colchester, C04 3SQ, UK

    David Gamez

Authors
  1. David Gamez
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Editor information

Joaquim Marques de Sá Luís A. Alexandre Włodzisław Duch Danilo Mandic

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© 2007 Springer-Verlag Berlin Heidelberg

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Gamez, D. (2007). SpikeStream: A Fast and Flexible Simulator of Spiking Neural Networks. In: de Sá, J.M., Alexandre, L.A., Duch, W., Mandic, D. (eds) Artificial Neural Networks – ICANN 2007. ICANN 2007. Lecture Notes in Computer Science, vol 4668. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74690-4_37

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  • DOI: https://doi.org/10.1007/978-3-540-74690-4_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74689-8

  • Online ISBN: 978-3-540-74690-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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