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Brian: a simple and flexible simulator for spiking neural networks

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Romain Brette and Dan Goodman

1 July 2009

New neural-simulation technology makes spiking neuron models more accessible to systems neuroscience and neuromorphic engineering.




Authors

Romain Brette
CNRS, Ecole Normale Supérieure

Romain Brette is an assistant professor in computational neuroscience. His research interests include spike-based neural computation (especially in the auditory system), theory and simulation of spiking neuron models, and intracellular recording techniques.

Dan Goodman
CNRS, Ecole Normale Supérieure

Dan Goodman is a postdoctoral researcher in computational neuroscience. His research interests include the role of spike-timing based coding and computation, and neural simulation technologies.


References
  1. R. Brette, M. Rudolph, T. Carnevale, M. Hines, D. Beeman, J. M. Bower, M. Diesmann, A. Morrison, P. H. Goodman, F. C. Harris Jr., M. Zirpe, T. Natschläger, D. Pecevski, B. Ermentrout, M. Djurfeldt, A. Lansner, O. Rochel, T. Vieville, E. Muller, A. P. Dav, Simulation of networks of spiking neurons: a review of tools and strategies, J. Comp. Neurosci. 23 (3), pp. 349-98, 2007.

  2. http://www.briansimulator.org

  3. W. Stürzl, R. Kempter and J. L. van Hemmen, Theory of arachnid prey localization, Phys. Rev. Lett. 84 (24), pp. 5668-5671, 2000.

  4. D. Goodman and R. Brette, Brian: a simulator for spiking neural networks in Python, Frontiers in Neuroinformatics 2 (5), 2008.


 
DOI:  10.2417/1200907.1659

@NeuroEng



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