Spyke Viewer and the cloud: quick algorithm development and large scale data analysis for electrophysiology

Abstract

Event Abstract Back to Event Spyke Viewer and the cloud: quick algorithm development and large scale data analysis for electrophysiology Robert Pröpper1* 1 TU Berlin, Germany Effective analysis of the increasingly large amounts of data generated by current electrophysiological experiments and simulations requires powerful new tools. Spyke Viewer (Pröpper and Obermayer, 2013) is an open source, multi-platform application for navigating, visualizing and analyzing such data. Based on Python and the Neo framework (Garcia et al., 2014), Spyke Viewer supports reading and writing a wide variety of file formats. The loaded Neo object hierarchy is represented in a graphical object browser. Together with user-defined filters, the object browser is used to select data for visualization and analysis. Operations on the selected data can be performed using an integrated Python console or with plugins. Spyke Viewer includes a number of plugins for common plots and basic analyses. Users can easily create their own plugins using the integrated Python editor or external tools. Plugins are implemented as Python classes and can use any existing library. Spyke Viewer now supports executing plugins on computing or cloud servers using Celery [1]. Plugins, even with local code changes, can be submitted for remote execution with a single command. An arbitrary number of compute nodes can be used and new nodes can be added during runtime. Spyke Viewer includes a remote execution manager where users can manage queued, running and finished plugins or view parameters, progress and results. This allows quick iteration during development and simple execution even for large scale analyses. [1] http://www.celeryproject.org/ Figure 1 References (Garcia et al., 2014) Garcia, S., et al. "Neo: an object model for handling electrophysiology data in multiple formats." Frontiers in Neuroinformatics 8 (2014). (Pröpper and Obermayer, 2013) Pröpper, Robert, and Klaus Obermayer. "Spyke Viewer: a flexible and extensible platform for electrophysiological data analysis." Frontiers in Neuroinformatics 7 (2013). Keywords: Electrophysiology, data sharing, algorithm development, algorithm sharing, Neo, visualization, cloud Conference: Neuroinformatics 2014, Leiden, Netherlands, 25 Aug - 27 Aug, 2014. Presentation Type: Demo, not to be considered for oral presentation Topic: Electrophysiology Citation: Pröpper R (2014). Spyke Viewer and the cloud: quick algorithm development and large scale data analysis for electrophysiology. Front. Neuroinform. Conference Abstract: Neuroinformatics 2014. doi: 10.3389/conf.fninf.2014.18.00047 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 22 Apr 2014; Published Online: 04 Jun 2014. * Correspondence: Mr. Robert Pröpper, TU Berlin, Berlin, Germany, robert.proepper@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Robert Pröpper Google Robert Pröpper Google Scholar Robert Pröpper PubMed Robert Pröpper Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.