Simulation of networks of spiking neurons: a review of tools and strategies

Romain Brette, Michelle Rudolph, Ted Carnevale, Michael Hines, David Beeman, James M. Bower, Markus Diesmann, Abigail Morrison, Philip H. Goodman, Frederick C. Harris, Jr., Milind Zirpe, Thomas Natschlaeger, Dejan Pecevski, Bard Ermentrout, Mikael Djurfeldt, Anders Lansner, Olivier Rochel, Thierry Vieville, Eilif Muller, Andrew P. Davison, Sami El Boustani and Alain Destexhe

Journal of Computational Neuroscience 23: 349-398, 2007.

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Abstract:

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 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-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 integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.


Supplementary information

We have conceived a set of "benchmark" simulations consisting of networks of excitatory and inhibitory spiking neurons, using either Hodgkin-Huxley or Integrate-and-Fire mechanisms, conductance-based or current-based synapses, and clock-driven or event-driven simulation algorithms. These simulations were implemented in the different simulators and we provide the codes for all of them. These codes have been uploaded to the ModelDB database at http://senselab.med.yale.edu/SenseLab/ModelDB/ShowModel.asp?model=83319
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