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Brian: A Simulator for Spiking Neural Networks in Python

“Brian” is a new simulator for spiking neural networks, written in Python (http://brian. di.ens.fr). It is an intuitive and highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can defin...

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Detalles Bibliográficos
Autores principales: Goodman, Dan, Brette, Romain
Formato: Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2605403/
https://www.ncbi.nlm.nih.gov/pubmed/19115011
http://dx.doi.org/10.3389/neuro.11.005.2008
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author Goodman, Dan
Brette, Romain
author_facet Goodman, Dan
Brette, Romain
author_sort Goodman, Dan
collection PubMed
description “Brian” is a new simulator for spiking neural networks, written in Python (http://brian. di.ens.fr). It is an intuitive and highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries can also be used for defining models and analysing data. Vectorisation techniques allow efficient simulations despite the overheads of an interpreted language. Brian will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations. With its easy and intuitive syntax, Brian is also very well suited for teaching computational neuroscience.
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spelling pubmed-26054032009-01-07 Brian: A Simulator for Spiking Neural Networks in Python Goodman, Dan Brette, Romain Front Neuroinformatics Neuroscience “Brian” is a new simulator for spiking neural networks, written in Python (http://brian. di.ens.fr). It is an intuitive and highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries can also be used for defining models and analysing data. Vectorisation techniques allow efficient simulations despite the overheads of an interpreted language. Brian will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations. With its easy and intuitive syntax, Brian is also very well suited for teaching computational neuroscience. Frontiers Research Foundation 2008-11-18 /pmc/articles/PMC2605403/ /pubmed/19115011 http://dx.doi.org/10.3389/neuro.11.005.2008 Text en Copyright © 2008 Goodman and Brette. http://www.frontiersin.org/licenseagreement This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.
spellingShingle Neuroscience
Goodman, Dan
Brette, Romain
Brian: A Simulator for Spiking Neural Networks in Python
title Brian: A Simulator for Spiking Neural Networks in Python
title_full Brian: A Simulator for Spiking Neural Networks in Python
title_fullStr Brian: A Simulator for Spiking Neural Networks in Python
title_full_unstemmed Brian: A Simulator for Spiking Neural Networks in Python
title_short Brian: A Simulator for Spiking Neural Networks in Python
title_sort brian: a simulator for spiking neural networks in python
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2605403/
https://www.ncbi.nlm.nih.gov/pubmed/19115011
http://dx.doi.org/10.3389/neuro.11.005.2008
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