OpenElectrophy: an electrophysiological data- and analysis-sharing framework

Samuel Garcia (1) , Nicolas Fourcaud-Trocmé (1)

1 Neurosciences Sensorielles Comportement Cognition

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. Based on the object-oriented language Python, it stores all experiment data and meta-data in a single central SQL-type database. It also 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 method due to Roux et. al. [1]. OpenElectrophy is open-source and is freely available for download at http://neuralensemble.org/trac/OpenElectrophy.

Mots clés: Others; BMI and signal processing; Oscillation and synchronization; Action selection

Domaines: Neurosciences [q-bio.NC]; Neurosciences

Samuel Garcia, Nicolas Fourcaud-Trocmé. OpenElectrophy: an electrophysiological data- and analysis-sharing framework. Cinquième conférence plénière française de Neurosciences Computationnelles, "Neurocomp'10", Aug 2010, Lyon, France. ⟨hal-00553414⟩