Original Research ARTICLE

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OpenElectrophy: an electrophysiological data- and analysis-sharing framework


Neurosciences Sensorielles Comportement Cognition, CNRS – UMR5020 – Université Claude Bernard Lyon 1, Lyon, France
Progress in experimental tools and design is allowing the acquisition of increasingly large datasets. Storage, manipulation and efficient analyses of such large amounts of data is now a primary issue. We present OpenElectrophy, an electrophysiological data- and analysis-sharing framework developed to fill this niche. It stores all experiment data and meta-data in a single central MySQL database, and provides a graphic user interface to visualize and explore the data, and a library of functions for user analysis scripting in Python. It implements multiple spike-sorting methods, and oscillation detection based on the ridge extraction methods due to Roux et al. (2007). OpenElectrophy is open source and is freely available for download at http://neuralensemble.org/trac/OpenElectrophy.
Keywords:
python, electrophysiology, analysis, oscillation, spike sorting, database, SQL
Citation:
Garcia S and Fourcaud-Trocmé N (2009). OpenElectrophy: an electrophysiological data- and analysis-sharing framework. Front. Neuroinform. 3:14. doi: 10.3389/neuro.11.014.2009
Received:
12 September 2008;
 Paper pending published:
27 October 2008;
Accepted:
30 April 2009;
 Published online:
27 May 2009.

Edited by:

Rolf Kötter, Radboud University Nijmegen, The Netherlands

Reviewed by:

Robert Oostenveld, Cognition and Behaviour Centre for Cognitive Neuroimaging, The Netherlands
Eilif Muller, Brain Mind Institute, EPFL, Switzerland
Copyright:
© 2009 Garcia and Fourcaud-Trocmé. 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:
Samuel Garcia, Laboratoire de Neurosciences Sensorielles Comportement Cognition, CNRS – UMR5020 – Université Claude Bernard Lyon 1, Equipe logistique et technique, 50 Avenue Tony Garnier, 69366 Lyon Cedex 07, France. e-mail: sgarcia@olfac.univ-lyon1.fr
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