Analyzing electrophysiology and simulation data with Spyke Viewer
The amount of data generated by electrophysiological experiments and simulations continues to increase. In order to analyze these datasets, researchers need a way to navigate, access and visualize data in various formats. The development environment for new analyses should enable rapid iteration without restricting flexibility. There should be a convenient way to share newly developed analyses and visualizations with collaborators or the community.
We address these requirements with Spyke Viewer [1], an open source, multi-platform graphical user interface (GUI) application for navigating, visualizing and analyzing electrophysiological datasets. It is based on Python and the Neo framework [2], which enables it to load a wide variety of file formats commonly used in electrophysiology. Using Spyke Viewer, researchers can load and navigate Neo object hierarchies and easily perform operations on the data.
The central design goals of Spyke Viewer are flexibility and extensibility. An embedded Python console allows for interactive exploration of selected data subsets. Users can create filters to control how the data is represented in the navigation view. The filters are regular Python functions that can be edited directly from the GUI. They are stored as annotated Python files so they can be modified using external editors and shared with other users.
A plugin architecture enables users to extend Spyke Viewer. Plugins can be easily created and modified using the integrated Python editor. They are implemented as Python classes, so they can use any existing Python libraries. Analysis plugins can range from simple plots to elaborate analyses and support quick and easy creation of graphical parameter editors using guidata [3]. Spyke Viewer includes several plugins for commonly used plots such as spectrograms, peristimulus time histograms or cross-correlograms. Analysis plugins can also be executed independently of the GUI, e.g. to run on compute servers. Using IO plugins, Spyke Viewer can load file formats and data sources that are not supported by Neo.
While various tools for analyzing electrophysiological data exist, none offer the flexibility of Spyke Viewer. Many are limited to certain file formats or analysis methods and based on proprietary software. In contrast, Spyke Viewer is open source and can run custom analyses with data from arbitrary sources thanks to its plugin system. Users can rapidly develop new analyses and easily share them with the community using a web-based plugin repository.
[1] http://spyke-viewer.readthedocs.org
[2] http://neuralensemble.org/neo/
[3] https://code.google.com/p/guidata/
Acknowledgements
Felix Franke for an earlier iteration of the program
Philipp Meier for simulated test and demonstration data
Keywords:
Electrophysiology,
data sharing,
algorithm development,
algorithm sharing,
Neo,
Windows,
Linux,
OS X,
visualization
Conference:
Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, 2013.
Presentation Type:
Demo
Topic:
Electrophysiology
Citation:
Pröpper
R and
Obermayer
K
(2013). Analyzing electrophysiology and simulation data with Spyke Viewer.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2013.
doi: 10.3389/conf.fninf.2013.09.00047
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Received:
29 Apr 2013;
Published Online:
11 Jul 2013.
*
Correspondence:
Mr. Robert Pröpper, TU Berlin, Berlin, Germany, robert.proepper@gmail.com