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Trends in Programming Languages for Neuroscience Simulations

Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accuratel...

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Detalles Bibliográficos
Autores principales: Davison, Andrew P., Hines, Michael L., Muller, Eilif
Formato: Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2796921/
https://www.ncbi.nlm.nih.gov/pubmed/20198154
http://dx.doi.org/10.3389/neuro.01.036.2009
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author Davison, Andrew P.
Hines, Michael L.
Muller, Eilif
author_facet Davison, Andrew P.
Hines, Michael L.
Muller, Eilif
author_sort Davison, Andrew P.
collection PubMed
description Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accurately translating ideas into a working simulation. We review long-term trends in the development of programmable simulator interfaces, and examine the benefits of moving from proprietary, domain-specific languages to modern dynamic general-purpose languages, in particular Python, which provide neuroscientists with an interactive and expressive simulation development environment and easy access to state-of-the-art general-purpose tools for scientific computing.
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spelling pubmed-27969212010-03-02 Trends in Programming Languages for Neuroscience Simulations Davison, Andrew P. Hines, Michael L. Muller, Eilif Front Neurosci Neuroscience Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accurately translating ideas into a working simulation. We review long-term trends in the development of programmable simulator interfaces, and examine the benefits of moving from proprietary, domain-specific languages to modern dynamic general-purpose languages, in particular Python, which provide neuroscientists with an interactive and expressive simulation development environment and easy access to state-of-the-art general-purpose tools for scientific computing. Frontiers Research Foundation 2009-12-15 /pmc/articles/PMC2796921/ /pubmed/20198154 http://dx.doi.org/10.3389/neuro.01.036.2009 Text en Copyright © 2009 Davison, Hines and Muller. 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
Davison, Andrew P.
Hines, Michael L.
Muller, Eilif
Trends in Programming Languages for Neuroscience Simulations
title Trends in Programming Languages for Neuroscience Simulations
title_full Trends in Programming Languages for Neuroscience Simulations
title_fullStr Trends in Programming Languages for Neuroscience Simulations
title_full_unstemmed Trends in Programming Languages for Neuroscience Simulations
title_short Trends in Programming Languages for Neuroscience Simulations
title_sort trends in programming languages for neuroscience simulations
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2796921/
https://www.ncbi.nlm.nih.gov/pubmed/20198154
http://dx.doi.org/10.3389/neuro.01.036.2009
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