Simulation ot network of spiking neuros: A review of tools and strategies

Author(s) Romain Brette
Milind Zirpe
Thomas Natschläger
Dejan Pecevski
Bard Ermentrout
Mikael Djurfeldt
Andreas Lasner
Olivier Rochel
Thierry Vieville
Eilif Muller
Andrew Davison
Michelle Rudolph
Sami El Boustani
Alain Destexhe
Ted Cernevale
Michael Hines
David Beeman
James M. Bower
Markus Diemann
Philip H. Goodman
Frederick C. Harris, Jr.
Title Simulation ot network of spiking neuros: A review of tools and strategies
Typ Article
Month December
Year 2007
Journal Journal fof Cumputational Neuroscience
Volume 23
Pages 349-398
Number 3
SCCH # 0637
We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that 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 fully 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, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-based or event-based 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 integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.