"Brian" is a simulator for spiking neural networks
(http://www.briansimulator.org). The focus is on making the
writing of simulation code as quick and easy as possible for
the user, and on flexibility: new and non-standard models are
no more difficult to define than standard ones. This allows
scientists to spend more time on the details of their models,
and less on their implementation. Neuron models are defined by
writing differential equations in standard mathematical
notation, facilitating scientific communication. Brian is
written in the Python programming language, and uses
vector-based computation to allow for efficient
simulations. It is particularly useful for neuroscientific
modelling at the systems level, and for teaching computational
neuroscience.
%0 Journal Article
%1 goodman_brian_2009
%A Goodman, Dan F. M.
%A Brette, Romain
%D 2009
%J Frontiers in Neuroscience
%K python simulation
%R 10.3389/neuro.01.026.2009
%T The Brian Simulator
%U http://frontiersin.org/neuroscience/paper/10.3389/neuro.01/026.2009/
%X "Brian" is a simulator for spiking neural networks
(http://www.briansimulator.org). The focus is on making the
writing of simulation code as quick and easy as possible for
the user, and on flexibility: new and non-standard models are
no more difficult to define than standard ones. This allows
scientists to spend more time on the details of their models,
and less on their implementation. Neuron models are defined by
writing differential equations in standard mathematical
notation, facilitating scientific communication. Brian is
written in the Python programming language, and uses
vector-based computation to allow for efficient
simulations. It is particularly useful for neuroscientific
modelling at the systems level, and for teaching computational
neuroscience.
@article{goodman_brian_2009,
abstract = {{"Brian"} is a simulator for spiking neural networks
(http://www.briansimulator.org). The focus is on making the
writing of simulation code as quick and easy as possible for
the user, and on flexibility: new and non-standard models are
no more difficult to define than standard ones. This allows
scientists to spend more time on the details of their models,
and less on their implementation. Neuron models are defined by
writing differential equations in standard mathematical
notation, facilitating scientific communication. Brian is
written in the Python programming language, and uses
vector-based computation to allow for efficient
simulations. It is particularly useful for neuroscientific
modelling at the systems level, and for teaching computational
neuroscience.},
added-at = {2014-01-19T08:31:51.000+0100},
author = {Goodman, Dan F. M. and Brette, Romain},
bdsk-url-1 = {http://frontiersin.org/neuroscience/paper/10.3389/neuro.01/026.2009/},
bdsk-url-2 = {http://dx.doi.org/10.3389/neuro.01.026.2009},
biburl = {https://www.bibsonomy.org/bibtex/20f58ff81c7843742b51f594ed8e25629/neurokernel},
doi = {10.3389/neuro.01.026.2009},
interhash = {58d090d082871b722ec85e0aa0105a7b},
intrahash = {0f58ff81c7843742b51f594ed8e25629},
journal = {Frontiers in Neuroscience},
keywords = {python simulation},
month = sep,
timestamp = {2014-01-19T08:31:51.000+0100},
title = {The {Brian} Simulator},
url = {http://frontiersin.org/neuroscience/paper/10.3389/neuro.01/026.2009/},
year = 2009
}