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Neural Comput. 2011 Jun;23(6):1503-35. doi: 10.1162/NECO_a_00123. Epub 2011 Mar 11.

Vectorized algorithms for spiking neural network simulation.

Author information

Laboratoire Psychologie de la Perception, CNRS and Université Paris Descartes, Paris 75006, France, and Département d'Etudes Cognitives, Ecole Normale Supérieure, Paris Cedex 05, 75230 France.


High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages.

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