Good practice for conducting and reporting MEG research

Research output: Contribution to journalArticleScientificpeer-review


  • Joachim Gross
  • Sylvain Baillet
  • Gareth R. Barnes
  • Richard N. Henson
  • Arjan Hillebrand
  • Ole Jensen
  • Karim Jerbi
  • Vladimir Litvak
  • Burkhard Maess
  • Robert Oostenveld
  • Lauri Parkkonen
  • Jason R. Taylor
  • Virginie van Wassenhovek
  • Michael Wibraln
  • Jan-Mathjis Schoffelen

Research units


Magnetoencephalographic (MEG) recordings are a rich source of information about the neural dynamics underlying cognitive processes in the brain, with excellent temporal and good spatial resolution. In recent years there have been considerable advances in MEG hardware developments and methods. Sophisticated analysis techniques are now routinely applied and continuously improved, leading to fascinating insights into the intricate dynamics of neural processes. However, the rapidly increasing level of complexity of the different steps in a MEG study make it difficult for novices, and sometimes even for experts, to stay aware of possible limitations and caveats. Furthermore, the complexity of MEG data acquisition and data analysis requires special attention when describing MEG studies in publications, in order to facilitate interpretation and reproduction of the results. This manuscript aims at making recommendations for a number of important data acquisition and data analysis steps and suggests details that should be specified in manuscripts reporting MEG studies. These recommendations will hopefully serve as guidelines that help to strengthen the position of the MEG research community within the field of neuroscience, and may foster discussion in order to further enhance the quality and impact of MEG research.


Original languageEnglish
Pages (from-to)349-363
Publication statusPublished - 2013
MoE publication typeA1 Journal article-refereed

    Research areas

  • Magnetoencephalography, MEG, Acquisition, Analysis, Connectivity, Source localization, Guidelines, Recommendations, Reproducible research, Spectral analysis

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