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Towards an objective evaluation of EEG/MEG source estimation methods - The linear approach.

Olaf Hauk1, Matti Stenroos2, Matthias S Treder3

  • 1MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK.

Neuroimage
|April 7, 2022
PubMed
Summary

This study introduces a new framework for evaluating EEG/MEG source estimation methods, focusing on spatial resolution and leakage. The findings highlight limitations in current methods, especially for deep brain activity, urging further research and adoption of objective analysis tools.

Keywords:
BeamformingCross-talk functionInverse problemLocalization errorMinimum-norm estimationPoint-spread functionResolution matrixSpatial deviationSpatial filter

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Spatial resolution in EEG/MEG source estimation is limited by source leakage.
  • Existing software offers many methods but lacks tools for objective evaluation and comparison.
  • Experimental researchers need intuitive tools to assess the performance of source estimation techniques.

Purpose of the Study:

  • To present a framework and tools for objective resolution analysis of EEG/MEG source estimation methods.
  • To evaluate widely used methods like L2-MNE and LCMV beamformers using defined resolution metrics.
  • To provide a tutorial for experimental researchers on linear EEG/MEG source estimation and resolution analysis.

Main Methods:

  • Developed a framework based on linear systems analysis for resolution analysis.
  • Defined key resolution metrics: Peak Localization Error (PLE) and Spatial Deviation (SD).
  • Utilized the resolution matrix, including point-spread (PSF) and cross-talk (CTF) functions, to characterize source leakage.

Main Results:

  • Some methods achieved low or zero PLE for PSFs, indicating good localization accuracy in ideal cases.
  • All evaluated methods showed suboptimal Spatial Deviation (SD) and performance on cross-talk functions (CTFs).
  • Performance was particularly limited for deep cortical areas across all methods.

Conclusions:

  • The developed framework and tools enable objective comparison of EEG/MEG source estimation methods.
  • Current linear methods have inherent limitations in spatial resolution and leakage, especially for deeper sources.
  • Encourages wider adoption of resolution analysis to improve the reliability of EEG/MEG source estimation in research.