Journal:Handling metadata in a neurophysiology laboratory

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Full article title Handling metadata in a neurophysiology laboratory
Journal Frontiers in Neuroinformatics
Author(s) Zehl, Lyuba; Jaillet, Florent; Stoewer, Adrian; Grewe, Jan; Sobolev, Andrey; Wachtler, Thomas; Brochier, Thomas G.; Riehle, Alexa; Denker, Michael; Grün, Sonja
Author affiliation(s) Jülich Research Centre, Aix-Marseille Université, Ludwig-Maximilians-Universität München, Eberhard-Karls-Universität Tübingen, Aachen University
Primary contact Email: l dot zehl at fz-juelich dot de
Editors Luo, Qingming
Year published 2016
Volume and issue 10
Page(s) 26
DOI 10.3389/fninf.2016.00026
ISSN 1662-5196
Distribution license Creative Commons Attribution 4.0 International
Website https://www.frontiersin.org/articles/10.3389/fninf.2016.00026/full
Download 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[1][2][3] in combination with sophisticated stimulation methods, such as optogenetics.[4][5] In addition, recordings can be performed in parallel from multiple brain areas, together with behavioral measures such as eye or limb movements.[6][7] Such recordings enable researchers to study network interactions and cross-area coupling, and to relate neuronal processing to the behavioral performance of the subject.[8][9][10] These approaches lead to increasingly complex experimental designs that are difficult to parameterize, e.g., due to multidimensional characterization of natural stimuli[11] or high-dimensional movement parameters for almost freely behaving subjects.[12] 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.[13][14][15] 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

  1. ↑ Nicolelis, M.A.; Ribeiro, S. (2002). "Multielectrode recordings: The next steps". Current Opinion in Neurobiology 12 (5): 602–6. doi:10.1016/S0959-4388(02)00374-4. PMID 12367642. 
  2. ↑ Verkhratsky, A.; Krishtal, O.A.; Petersen, O.H. (2006). "From Galvani to patch clamp: The development of electrophysiology". Pflügers Archiv 453 (3): 233–47. doi:10.1007/s00424-006-0169-z. PMID 17072639. 
  3. ↑ Obien, M.E.; Deligkaris, K.; Bullmann, T. et al. (2015). "Revealing neuronal function through microelectrode array recordings". Frontiers in Neuroscience 8: 423. doi:10.3389/fnins.2014.00423. PMC PMC4285113. PMID 25610364. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4285113. 
  4. ↑ Deisseroth, K.; Schnitzer, M.J. (2013). "Engineering approaches to illuminating brain structure and dynamics". Neuron 80 (3): 568–77. doi:10.1016/j.neuron.2013.10.032. PMC PMC5731466. PMID 24183010. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5731466. 
  5. ↑ Miyamoto, D.; Murayama, M. (2016). "The fiber-optic imaging and manipulation of neural activity during animal behavior". Neuroscience Research 103: 1–9. doi:10.1016/j.neures.2015.09.004. PMID 26427958. 
  6. ↑ Maldonado, P.; Babul, C.; Singer, W. et al. (2008). "Synchronization of neuronal responses in primary visual cortex of monkeys viewing natural images". Journal of Neurophysiology 100 (3): 1523-32. doi:10.1152/jn.00076.2008. PMID 18562559. 
  7. ↑ Vargas-Irwin, C.E.; Shakhnarovich, G.; Yadollahpour, P. et al. (2010). "Decoding complete reach and grasp actions from local primary motor cortex populations". Journal of Neuroscience 30 (29): 9659-69. doi:10.1523/JNEUROSCI.5443-09.2010. PMC PMC2921895. PMID 20660249. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2921895. 
  8. ↑ Berényi, A.; Somogyvári, Z.; Nagy, A.J. et al. (2014). "Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals". Journal of Neurophysiology 111 (5): 1132-49. doi:10.1152/jn.00785.2013. PMC PMC3949233. PMID 24353300. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3949233. 
  9. ↑ Lewis, C.M.; Bosman, C.A.; Fries, P. et al. (2015). "Recording of brain activity across spatial scales". Current Opinion in Neurobiology 32: 68–77. doi:10.1016/j.conb.2014.12.007. PMID 25544724. 
  10. ↑ Lisman, J. (2015). "The challenge of understanding the brain: Where we stand in 2015". Neuron 86 (4): 864-882. doi:10.1016/j.neuron.2015.03.032. PMC PMC4441769. PMID 25996132. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4441769. 
  11. ↑ Geisler, W.S. (2008). "Visual perception and the statistical properties of natural scenes". Annual Review of Psychology 59: 167–92. doi:10.1146/annurev.psych.58.110405.085632. PMID 17705683. 
  12. ↑ Schwarz, D.A.; Lebedev, M.A.; Hanson, T.L. et al. (2014). "Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys". Nature Methods 11 (6): 670-6. doi:10.1038/nmeth.2936. PMC PMC4161037. PMID 24776634. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4161037. 
  13. ↑ Laine, C.; Goodman, S.N.; Griswold, M.E.; Sox, H.C. (2007). "Reproducible research: Moving toward research the public can really trust". Annals of Internal Medicine 146 (6): 450–3. doi:10.7326/0003-4819-146-6-200703200-00154. PMID 17339612. 
  14. ↑ Peng, R.D. (2011). "Reproducible research in computational science". Science 334 (6060): 1226-7. doi:10.1126/science.1213847. PMC PMC3383002. PMID 22144613. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3383002. 
  15. ↑ Tomasello, M.; Call, J. (2011). "Methodological challenges in the study of primate cognition". Science 334 (6060): 1227-8. doi:10.1126/science.1213443. PMID 22144614. 

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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