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Focused Review ARTICLE

Trends in programming languages for neuroscience simulations

Andrew P. Davison^1*, Michael L. Hines² and Eilif Muller³

Unité de Neurosciences Intégratives et Computationnelles, Centre National de la Recherche Scientifique, Gif sur Yvette, France

Computer Science, Yale University, New Haven, CT, USA

Laboratory for Computational Neuroscience, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

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.

Keywords:

Python, simulation, computational neuroscience

Citation:

Davison AP, Hines M and Muller E (2009). Trends in programming languages for neuroscience simulations.Front. Neurosci. 3,3:374- 380. doi: 10.3389/neuro.01.036.2009

Received:

31 July 2009;

Paper pending published:

04 September 2009;

Accepted:

02 October 2009;

Published online:

15 December 2009.

Edited by:

Rolf Kötter, Radboud University Nijmegen, The Netherlands

Reviewed by:

Felix Schürmann, Ecole Polytechnique Fédérale de Lausanne, Switzerland
Marc-Oliver Gewaltig, Honda Research Institute Europe GmbH, Germany
Volker Steuber, University of Hertfordshire, UK

© 2009 Davison, Hines and Muller. 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.

*Correspondence:

Andrew Davison, UNIC, BÃƒÂ¢t. 32/33, CNRS, 1 Avenue de la Terrasse, 91198 Gif sur Yvette, France. andrew.davison@unic.cnrs-gif.fr