View source for Journal:Handling metadata in a neurophysiology laboratory

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|title_full   = Handling metadata in a neurophysiology laboratory
|journal      = ''Frontiers in Neuroinformatics''
|authors      = Zehl, Lyuba; Jaillet, Florent; Stoewer, Adrian; Grewe, Jan; Sobolev, Andrey; Wachtler, Thomas; Brochier, Thomas G.; Riehle, Alexa; Denker, Michael; Grün, Sonja
|affiliations = Jülich Research Centre, Aix-Marseille Université, Ludwig-Maximilians-Universität München, Eberhard-Karls-Universität Tübingen, Aachen University
|contact      = Email: l dot zehl at fz-juelich dot de
|editors      = Luo, Qingming
|pub_year     = 2016
|vol_iss      = '''10'''
|pages        = 26
|doi          = [http://10.3389/fninf.2016.00026 10.3389/fninf.2016.00026]
|issn         = 1662-5196
|license      = [http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International]
|website      = [https://www.frontiersin.org/articles/10.3389/fninf.2016.00026/full https://www.frontiersin.org/articles/10.3389/fninf.2016.00026/full]
|download     = [https://www.frontiersin.org/articles/10.3389/fninf.2016.00026/pdf https://www.frontiersin.org/articles/10.3389/fninf.2016.00026/pdf] (PDF)
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==Abstract==
To date, non-reproducibility of neurophysiological research is a matter of intense discussion in the scientific community. A crucial component to enhance reproducibility is to comprehensively collect and store metadata, that is, all information about the experiment, the data, and the applied preprocessing steps on the data, such that they can be accessed and shared in a consistent and simple manner. However, the complexity of experiments, the highly specialized analysis workflows, and a lack of knowledge on how to make use of supporting software tools often overburden researchers to perform such a detailed documentation. For this reason, the collected metadata are often incomplete, incomprehensible for outsiders, or ambiguous. Based on our research experience in dealing with diverse datasets, we here provide conceptual and technical guidance to overcome the challenges associated with the collection, organization, and storage of metadata in a neurophysiology [[laboratory]]. Through the concrete example of managing the metadata of a complex experiment that yields multi-channel recordings from monkeys performing a behavioral motor task, we practically demonstrate the implementation of these approaches and solutions, with the intention that they may be generalized to other projects. Moreover, we detail five use cases that demonstrate the resulting benefits of constructing a well-organized metadata collection when processing or analyzing the recorded data, in particular when these are shared between laboratories in a modern scientific collaboration. Finally, we suggest an adaptable workflow to accumulate, structure and store metadata from different sources using, by way of example, the odML metadata framework.

==Introduction==
Technological advances in neuroscience during the last decades have led to methods that nowadays enable researchers to simultaneously record the activity from tens to hundreds of neurons simultaneously, in vitro or in vivo, using a variety of techniques<ref name="NicolelisMulti02">{{cite journal |title=Multielectrode recordings: The next steps |journal=Current Opinion in Neurobiology |author=Nicolelis, M.A.; Ribeiro, S. |volume=12 |issue=5 |pages=602–6 |year=2002 |doi=10.1016/S0959-4388(02)00374-4 |pmid=12367642}}</ref><ref name="VerkhratskyFrom06">{{cite journal |title=From Galvani to patch clamp: The development of electrophysiology |journal=Pflügers Archiv |author=Verkhratsky, A.; Krishtal, O.A.; Petersen, O.H. |volume=453 |issue=3 |pages=233–47 |year=2006 |doi=10.1007/s00424-006-0169-z |pmid=17072639}}</ref><ref name="ObienRevealing15">{{cite journal |title=Revealing neuronal function through microelectrode array recordings |journal=Frontiers in Neuroscience |author=Obien, M.E.; Deligkaris, K.; Bullmann, T. et al. |volume=8  |pages=423 |year=2015 |doi=10.3389/fnins.2014.00423 |pmid=25610364 |pmc=PMC4285113}}</ref> in combination with sophisticated stimulation methods, such as optogenetics.<ref name="DeisserothEngineer13">{{cite journal |title=Engineering approaches to illuminating brain structure and dynamics |journal=Neuron |author=Deisseroth, K.; Schnitzer, M.J. |volume=80 |issue=3 |pages=568–77 |year=2013 |doi=10.1016/j.neuron.2013.10.032 |pmid=24183010 |pmc=PMC5731466}}</ref><ref name="MiyamotoTheFiber16">{{cite journal |title=The fiber-optic imaging and manipulation of neural activity during animal behavior |journal=Neuroscience Research |author=Miyamoto, D.; Murayama, M. |volume=103 |pages=1–9 |year=2016 |doi=10.1016/j.neures.2015.09.004 |pmid=26427958}}</ref> In addition, recordings can be performed in parallel from multiple brain areas, together with behavioral measures such as eye or limb movements.<ref name="MaldonadoSynchro08">{{cite journal |title=Synchronization of neuronal responses in primary visual cortex of monkeys viewing natural images |journal=Journal of Neurophysiology |author=Maldonado, P.; Babul, C.; Singer, W. et al. |volume=100 |issue=3 |pages=1523-32 |year=2008 |doi=10.1152/jn.00076.2008 |pmid=18562559}}</ref><ref name="VargasIrwinDecoding10">{{cite journal |title=Decoding complete reach and grasp actions from local primary motor cortex populations |journal=Journal of Neuroscience |author=Vargas-Irwin, C.E.; Shakhnarovich, G.; Yadollahpour, P. et al. |volume=30 |issue=29 |pages=9659-69 |year=2010 |doi=10.1523/JNEUROSCI.5443-09.2010 |pmid=20660249 |pmc=PMC2921895}}</ref> Such recordings enable researchers to study network interactions and cross-area coupling, and to relate neuronal processing to the behavioral performance of the subject.<ref name="BerenyiLarge14">{{cite journal |title=Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals |journal=Journal of Neurophysiology |author=Berényi, A.; Somogyvári, Z.; Nagy, A.J. et al. |volume=111 |issue=5 |pages=1132-49 |year=2014 |doi=10.1152/jn.00785.2013 |pmid=24353300 |pmc=PMC3949233}}</ref><ref name="LewisRecording15">{{cite journal |title=Recording of brain activity across spatial scales |journal=Current Opinion in Neurobiology |author=Lewis, C.M.; Bosman, C.A.; Fries, P. et al. |volume=32 |pages=68–77 |year=2015 |doi=10.1016/j.conb.2014.12.007 |pmid=25544724}}</ref><ref name="LismanTheChall15">{{cite journal |title=The challenge of understanding the brain: Where we stand in 2015 |journal=Neuron |author=Lisman, J. |volume=86 |issue=4 |pages=864-882 |year=2015 |doi=10.1016/j.neuron.2015.03.032 |pmid=25996132 |pmc=PMC4441769}}</ref> These approaches lead to increasingly complex experimental designs that are difficult to parameterize, e.g., due to multidimensional characterization of natural stimuli<ref name="GeislerVisual08">{{cite journal |title=Visual perception and the statistical properties of natural scenes |journal=Annual Review of Psychology |author=Geisler, W.S. |volume=59 |pages=167–92 |year=2008 |doi=10.1146/annurev.psych.58.110405.085632 |pmid=17705683}}</ref> or high-dimensional movement parameters for almost freely behaving subjects.<ref name="SchwarzChronic14">{{cite journal |title=Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys |journal=Nature Methods |author=Schwarz, D.A.; Lebedev, M.A.; Hanson, T.L. et al. |volume=11 |issue=6 |pages=670-6 |year=2014 |doi=10.1038/nmeth.2936 |pmid=24776634 |pmc=PMC4161037}}</ref> It is a serious challenge for researchers to keep track of the overwhelming amount of metadata generated at each experimental step and to precisely extract all the information relevant for data analysis and interpretation of results. Various aspects such as the parametrization of the experimental task, filter settings and sampling rates of the setup, the quality of the recorded data, broken electrodes, preprocessing steps (e.g., spike sorting), or the condition of the subject need to be considered. Nevertheless, the organization of these metadata is of utmost importance for conducting research in a reproducible manner, i.e., the ability to faithfully reproduce the experimental procedures and subsequent analysis steps.<ref name="LaineReproduc07">{{cite journal |title=Reproducible research: Moving toward research the public can really trust |journal=Annals of Internal Medicine |author=Laine, C.; Goodman, S.N.; Griswold, M.E.; Sox, H.C. |volume=146 |issue=6 |pages=450–3 |year=2007 |doi=10.7326/0003-4819-146-6-200703200-00154 |pmid=17339612}}</ref><ref name="PengReproduc11">{{cite journal |title=Reproducible research in computational science |journal=Science |author=Peng, R.D. |volume=334 |issue=6060 |pages=1226-7 |year=2011 |doi=10.1126/science.1213847 |pmid=22144613 |pmc=PMC3383002}}</ref><ref name="TomaselloMethod11">{{cite journal |title=Methodological challenges in the study of primate cognition |journal=Science |author=Tomasello, M.; Call, J. |volume=334 |issue=6060 |pages=1227-8 |year=2011 |doi=10.1126/science.1213443 |pmid=22144614}}</ref> Moreover, detailed knowledge of the complete recording and analysis processes is crucial for the correct interpretation of results, and is a minimal requirement to enable researchers to verify published results and build their own research on the previous findings.

==References==
{{Reflist|colwidth=30em}}

==Notes==
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. The original article lists references alphabetically, but this version — by design — lists them in order of appearance. 

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