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Sharing individualised template MRI data for MEG source reconstruction: A solution for open data while keeping

Mikkel C Vinding1, Robert Oostenveld2

  • 1NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Nobels väg 9, D2, Stockholm 171 77, Sweden; Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.

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|April 4, 2022
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Summary

Individualized warped MRI templates enable sharing neuroimaging data for MEG source analysis while protecting participant anonymity. This method preserves analysis reproducibility and participant privacy.

Keywords:
AnonymisationData sharingMEGMRIPrivacySource reconstruction

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Area of Science:

  • Neuroimaging
  • Data Science
  • Biophysics

Background:

  • FAIR data sharing in neuroimaging is crucial but conflicts with participant anonymity due to identifiable anatomical MRI features.
  • Replicating MEG source analysis requires anatomical MRI data, posing privacy challenges.

Purpose of the Study:

  • To propose and validate a method using individualized warped MRI templates for MEG source analysis.
  • To ensure data sharing compliance with FAIR principles while safeguarding participant anonymity.

Main Methods:

  • Developed an individualized warped template method using open-source neuroimaging toolboxes.
  • Performed MEG source reconstruction using four methods with both original MRIs and warped templates.
  • Compared results for source reconstruction and morphological features (grey matter volume, surface area, cortical thickness, folding index).

Main Results:

  • MEG source reconstruction results showed high similarity for dipole fits and beamforming methods, and moderate similarity for minimum-norm estimates.
  • Warped templates maintained high similarity in grey matter volume and surface area compared to original MRIs.
  • Significant alteration in cortical thickness and folding index was observed, enhancing anonymity.

Conclusions:

  • Individualized warped MRI templates offer a viable compromise for sharing neuroimaging data for MEG analysis, preserving reproducibility and participant anonymity.
  • This approach facilitates FAIR data principles in neuroimaging research where direct MRI sharing is not feasible.