Handling complex metadata in neurophysiological experiments
-
1
Jülich Research Centre and JARA, Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6), Germany
-
2
Ludwig-Maximilians-Universität München, Biologie II, Germany
-
3
CNRS, Aix-Marseille Université, Institut de Neuroscience de la Timone (INT), France
-
4
RWTH Aachen Universität, Theoretical Systems Neurobiology, Germany
Technological progress in neuroscience allows to record from tens to hundreds of neurons simultaneously, both in vitro and in vivo, using various recording techniques and stimulation methods. In addition, recordings can be performed under more or less natural conditions in (almost) freely behaving animals. To disentangle the relationship between behavior and neuronal activity, it is necessary to document animal training, experimental procedures, and details of the setup along with the recorded neuronal and behavioral data. In consequence, electrophysiological experiments become increasingly complex. Given these various sources of complexity, the availability of all experimental metadata is of extreme relevance for reproducible data analysis and correct interpretation of results.
In order to provide metadata in an organized, human- and machine-readable way, an XML based file format, odML (open metadata Markup Language), was proposed [1]. We here demonstrate the usefulness of odML for data handling and analysis in the context of a complex behavioral experiment with neuronal recordings from a large number of electrodes delivering massively parallel spike and LFP data [2]. We illustrate the conceptual design of an odML metadata structure and offer templates to facilitate the usage of odML in different laboratories and experimental contexts. In addition, we demonstrate hands-on the advantages of using odML to screen large numbers of data sets according to selection criteria relevant for subsequent analyses. Well organized metadata management is a key component to guarantee reproducibility of experiments and to track provenance of performed analyses.
Acknowledgements
SMHB, HBP (EU grant 604102), G-Node (BMBF Grant 01GQ1302), BrainScaleS (EU Grant 269912), ANR-GRASP, Neuro_IC2010, CNRS-PEPS, RIKEN-CNRS Research Agreement.
References
[1] Grewe J, Wachtler T and Benda J (2011) A bottom-up approach to data annotation in neurophysiology. Front. Neuroinform. 5:16. doi: 10.3389/fninf.2011.00016
[2] Riehle A, Wirtssohn S, Grün S and Brochier T (2013) Mapping the spatio-temporal structure of motor cortical LFP and spiking activities during reach-to-grasp movements. Front. Neural Circuits 7:48. doi: 10.3389/fncir.2013.00048
Keywords:
odml,
metadata,
reproducibility,
multi-electrode-array,
complex behaviour
Conference:
Neuroinformatics 2014, Leiden, Netherlands, 25 Aug - 27 Aug, 2014.
Presentation Type:
Poster, not to be considered for oral presentation
Topic:
General neuroinformatics
Citation:
Zehl
L,
Denker
M,
Stoewer
A,
Jaillet
F,
Brochier
T,
Riehle
A,
Wachtler
T and
Grün
S
(2014). Handling complex metadata in neurophysiological experiments.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2014.
doi: 10.3389/conf.fninf.2014.18.00029
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:
04 Apr 2014;
Published Online:
04 Jun 2014.
*
Correspondence:
Ms. Lyuba Zehl, Jülich Research Centre and JARA, Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6), Jülich, Germany, lyuba.zehl@ebrains.eu