This title appears in the Scientific Report :
2018
Reproducible data analysis of activity data using open-source software toolsNeo & Elephant
Reproducible data analysis of activity data using open-source software toolsNeo & Elephant
The complexity of data from electrophysiological experiments is continuously increasing and has reached levels where novel concepts for data and metadata acquisition and management are essential for reproducible scientific work. Based on reproducible data generation and documentation, reproducibilit...
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Personal Name(s): | Sprenger, Julia (Corresponding author) |
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Yegenoglu, Alper / Denker, Michael / Grün, Sonja | |
Contributing Institute: |
Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 Computational and Systems Neuroscience; INM-6 |
Imprint: |
2018
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Conference: | Bernstein Conference 2018, Berlin (Germany), 2018-09-25 - 2018-09-29 |
Document Type: |
Poster |
Research Program: |
Kausative Mechanismen mesoskopischer Aktivitätsmuster in der auditorischen Kategorien-Diskrimination Human Brain Project Specific Grant Agreement 2 Human Brain Project Specific Grant Agreement 1 Supercomputing and Modelling for the Human Brain Connectivity and Activity |
Publikationsportal JuSER |
The complexity of data from electrophysiological experiments is continuously increasing and has reached levels where novel concepts for data and metadata acquisition and management are essential for reproducible scientific work. Based on reproducible data generation and documentation, reproducibility also needs to be implemented for subsequent processing steps like data preprocessing, analyisis and visualization [1,2]. Here, diverse tools from software development, general science and the domain of neuroscience can be successfully combined to form comprehensive data generation and analysis workflow.We present how three emerging open-source software tools can be successfully combined to form a collaborative analysis workflow for electrophysiology data: (i) data of different origins are represented in a standard form using the <I>Neo</I> framework [3], (ii) complex metadata accumulated in an electrophysiological experiment [4] are managed using the open metadata markup language (<I>odML</I>) [5] and (iii) analysis is performed utilizing the Electrophysiology Analysis Toolkit (<I>Elephant</I>, http://neuralensemble.org/elephant/). The <I>Elephant</I> tool is a recent community-centered analysis framework for multi-scale activity data. We highlight <I>Elephant</I> as modular software component that provides generic library functions to perform standard and advanced analysis processes focussing on statistical analysis of spiking activity but also covering analysis of LFP activity and the relation between the two.All these domain-specific tools are augmented by generic tools, such as data management platforms, version control systems and workflow management solutions, to form a blueprint for performing interdisciplinary, reproducible scientific research.References:[1] Badia, R. et al. (2015) INCF Program on Standards for data sharing: new perspectives on workflows and data management for the analysis of electrophysiological data. Techn. Report, https://www.incf.org/about-us/history/incf-scientific-workshops[2] Denker, M., Gruen, S. (2016). Designing Workflows for the Reproducible Analysis of Electrophysiological Data. In Brain-Inspired Computing, Amunts, K. et al., eds. (Cham: Springer International Publishing), pp. 58-72.[3] Garcia, S. et al. (2014) Neo: an object model for handling electrophysiology data in multiple formats. Front Neuroinf 8, 10.[4] Zehl, L. et al. (2016) Front Neuroinf, 10, 26.[5] Grewe, J. et al. (2011) Front Neuroinf 5, 16. |