Abstract | ||
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We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms th at are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, includ- ing Hodgkin-Huxley type, integrate-and-fire models, inter acting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integ ration strategy and simulation tool to use for a given modeling problem related to spiking neural networks. |
Year | DOI | Venue |
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2007 | 10.1007/s10827-007-0038-6 | Journal of Computational Neuroscience |
Keywords | DocType | Volume |
algorithms,computer simulation,hodgkin huxley,synapses,spiking neural network,neurosciences,electrophysiology | Journal | 23 |
Issue | ISSN | Citations |
3 | 0929-5313 | 241 |
PageRank | References | Authors |
16.03 | 60 | 22 |
Name | Order | Citations | PageRank |
---|---|---|---|
Romain Brette | 1 | 696 | 48.17 |
Michelle Rudolph | 2 | 282 | 20.15 |
Ted Carnevale | 3 | 254 | 18.08 |
Michael Hines | 4 | 355 | 24.07 |
David Beeman | 5 | 241 | 16.03 |
James M. Bower | 6 | 477 | 113.09 |
Markus Diesmann | 7 | 1692 | 129.76 |
Abigail Morrison | 8 | 761 | 53.95 |
Philip H. Goodman | 9 | 291 | 26.06 |
Frederick C. Harris Jr. | 10 | 547 | 78.86 |
Milind Zirpe | 11 | 241 | 16.03 |
T Natschläger | 12 | 1199 | 102.98 |
Dejan Pecevski | 13 | 391 | 24.75 |
Bard Ermentrout | 14 | 1098 | 161.49 |
Mikael Djurfeldt | 15 | 298 | 22.07 |
Anders Lansner | 16 | 647 | 100.03 |
Olivier Rochel | 17 | 274 | 19.93 |
Thierry Viéville | 18 | 376 | 36.35 |
Eilif Mueller | 19 | 247 | 16.65 |
Andrew P. Davison | 20 | 674 | 54.28 |
Sami El Boustani | 21 | 277 | 18.50 |
Alain Destexhe | 22 | 754 | 109.26 |