Start date should be earlier than end date. OK Please enter valid date format.

Original Research ARTICLE

This article is part of a Research Topic

NEURON and Python

Michael L. Hines¹, Andrew P. Davison²* and Eilif Muller³

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

Unité de Neurosciences Intégratives et Computationelles, CNRS, Gif sur Yvette, France

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

The NEURON simulation program now allows Python to be used, alone or in combination with NEURON's traditional Hoc interpreter. Adding Python to NEURON has the immediate benefit of making available a very extensive suite of analysis tools written for engineering and science. It also catalyzes NEURON software development by offering users a modern programming tool that is recognized for its flexibility and power to create and maintain complex programs. At the same time, nothing is lost because all existing models written in Hoc, including graphical user interface tools, continue to work without change and are also available within the Python context. An example of the benefits of Python availability is the use of the xml module in implementing NEURON's Import3D and CellBuild tools to read MorphML and NeuroML model specifications.

Keywords:

Python, simulation environment, computational neuroscience

Citation:

Hines ML, Davison AP and Muller E (2009). NEURON and Python. Front. Neuroinform. 3:1. doi: 10.3389/neuro.11.001.2009

Received:

24 September 2008;

Paper pending published:

21 October 2008;

Accepted:

05 January 2009;

Published online:

28 January 2009.

Edited by:

Rolf Kötter, Radboud University, Nijmegen, Netherlands

Reviewed by:

Felix Schürmann, Ecole Polytechnique Fédérale de Lausanne, Switzerland
Volker Steuber, University of Hertfordshire, UK
Arnd Roth, University College London, UK

© 2009 Hines, Davison 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, Bât. 32/33, CNRS, 1 Avenue de la Terrasse, 91198 Gif sur Yvette, France. e-mail: andrew.davison@unic.cnrs-gif.fr