Imperial College London

Dr Dan Goodman

Faculty of EngineeringDepartment of Electrical and Electronic Engineering




+44 (0)20 7594 6264d.goodman Website




1001Electrical EngineeringSouth Kensington Campus






BibTex format

author = {Brette, R and Goodman, DFM},
doi = {10.1162/NECO_a_00123},
journal = {Neural Comput},
pages = {1503--1535},
title = {Vectorized algorithms for spiking neural network simulation.},
url = {},
volume = {23},
year = {2011}

RIS format (EndNote, RefMan)

AB - 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.
AU - Brette,R
AU - Goodman,DFM
DO - 10.1162/NECO_a_00123
EP - 1535
PY - 2011///
SP - 1503
TI - Vectorized algorithms for spiking neural network simulation.
T2 - Neural Comput
UR -
UR -
VL - 23
ER -