000840027 001__ 840027
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000840027 037__ $$aFZJ-2017-07593
000840027 041__ $$aEnglish
000840027 1001_ $$0P:(DE-Juel1)161295$$aSprenger, Julia$$b0$$eCorresponding author
000840027 1112_ $$aThe 47th annual meeting of the Society for Neuroscience$$cWashington DC$$d2017-11-11 - 2017-11-15$$gSfN 2017$$wUSA
000840027 245__ $$aManagement of data and metadata - an exemplary electrophysiological workflow for collaborative data analysis
000840027 260__ $$c2017
000840027 3367_ $$033$$2EndNote$$aConference Paper
000840027 3367_ $$2BibTeX$$aINPROCEEDINGS
000840027 3367_ $$2DRIVER$$aconferenceObject
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000840027 3367_ $$0PUB:(DE-HGF)24$$2PUB:(DE-HGF)$$aPoster$$bposter$$mposter$$s1512122072_28147$$xAfter Call
000840027 520__ $$aThe complexity of neuroscientific experiments and their analysis has grown to a degree where special effort andattention is required to guarantee their reproducibility. In addition, collaborations across different laboratoriesand countries are becoming a standard work setting, which increases the need for comprehensivedocumentation of data and metadata, and explicit, formal descriptions of the data analysis process. Theavailability of software tools that support scientists in the various steps of this process is therefore indispensable[Denker and Grün (2016) In: Brain-Inspired Computing: Brain Comp 2015, Springer]. Moreover, it is necessary toestablish the workflows that link the various tools, and to develop simple interfaces for them.Here we demonstrate how such a reproducible, structured, and comprehensible workflow for anelectrophysiological experiment, covering the preparation, annotation and analysis data, can be set up in acollaborative environment by the combination of multiple state-of-the-art open-source projects. The workflowfeatures the Electrophysiology Analysis Toolkit (Elephant), which represents the central analysis resourceoffering methods ranging from the analysis of ensemble spike data to population signals, such as local fieldpotentials [http://neuralensemble.org/elephant/]. Elephant is based on the generic standardized datarepresentation for electrophysiological data provided by the Neo library [Garcia et al. (2014) Front Neuroinf8:10]. In addition, Neo is able to interface with a range of data formats commonly used in electrophysiology. Theopen metadata Markup Language (odML) is used as the hierarchical structure to store metadata related toelectrophysiological experiments [Grewe et al. (2011) Front Neuroinf 5:16]. Furthermore, odMLtables extendsthe accessibility of odML by providing an interface to a tabular metadata representation, e.g., using Excel[https://github.com/INM-6/python-odmltables]. Finally, NIX is a newly developed scheme designed to combineelectrophysiological data and metadata in a single, standardized format [https://github.com/G-Node/nix], andlinks the Neo and odML data models. We discuss multiple mechanisms that allow to describe the workflow itself,and show how it may be implemented, e.g., using the Collaboratory of the Human Brain Project[https://collab.humanbrainproject.eu]. While focusing on electrophysiology, many concepts of this workflow arealso transferable to different types of experimental environments.
000840027 536__ $$0G:(DE-HGF)POF3-571$$a571 - Connectivity and Activity (POF3-571)$$cPOF3-571$$fPOF III$$x0
000840027 536__ $$0G:(DE-Juel1)HGF-SMHB-2013-2017$$aSMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017)$$cHGF-SMHB-2013-2017$$fSMHB$$x1
000840027 536__ $$0G:(EU-Grant)720270$$aHBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270)$$c720270$$fH2020-Adhoc-2014-20$$x2
000840027 536__ $$0G:(GEPRIS)238707842$$aDFG project 238707842 - Kausative Mechanismen mesoskopischer Aktivitätsmuster in der auditorischen Kategorien-Diskrimination (238707842)$$c238707842$$x3
000840027 536__ $$0G:(GEPRIS)237833830$$aDFG project 237833830 - Optogenetische Analyse der für kognitive Fähigkeiten zuständigen präfrontal-hippokampalen Netzwerke in der Entwicklung (237833830)$$c237833830$$x4
000840027 536__ $$0G:(GEPRIS)238707842$$aDFG project 238707842 - Kausative Mechanismen mesoskopischer Aktivitätsmuster in der auditorischen Kategorien-Diskrimination (238707842)$$c238707842$$x5
000840027 7001_ $$0P:(DE-Juel1)161462$$aYegenoglu, Alper$$b1
000840027 7001_ $$0P:(DE-Juel1)144168$$aGrün, Sonja$$b2
000840027 7001_ $$0P:(DE-Juel1)144807$$aDenker, Michael$$b3$$eCorresponding author$$ufzj
000840027 909CO $$ooai:juser.fz-juelich.de:840027$$pec_fundedresources$$pVDB$$popenaire
000840027 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)161295$$aForschungszentrum Jülich$$b0$$kFZJ
000840027 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)161462$$aForschungszentrum Jülich$$b1$$kFZJ
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000840027 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144807$$aForschungszentrum Jülich$$b3$$kFZJ
000840027 9131_ $$0G:(DE-HGF)POF3-571$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vConnectivity and Activity$$x0
000840027 9141_ $$y2017
000840027 920__ $$lno
000840027 9201_ $$0I:(DE-Juel1)INM-10-20170113$$kINM-10$$lJara-Institut Brain structure-function relationships$$x0
000840027 9201_ $$0I:(DE-Juel1)INM-6-20090406$$kINM-6$$lComputational and Systems Neuroscience$$x1
000840027 9201_ $$0I:(DE-Juel1)IAS-6-20130828$$kIAS-6$$lTheoretical Neuroscience$$x2
000840027 980__ $$aposter
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