Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals

@article{Engemann2015AutomatedMS,
  title={Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals},
  author={Denis A. Engemann and Alexandre Gramfort},
  journal={NeuroImage},
  year={2015},
  volume={108},
  pages={328-42}
}
Magnetoencephalography and electroencephalography (M/EEG) measure non-invasively the weak electromagnetic fields induced by post-synaptic neural currents. The estimation of the spatial covariance of the signals recorded on M/EEG sensors is a building block of modern data analysis pipelines. Such covariance estimates are used in brain-computer interfaces (BCI) systems, in nearly all source localization methods for spatial whitening as well as for data covariance estimation in beamformers. The… CONTINUE READING
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Anatomically and Functionally Constrained Minimum-Norm Estimates. MEG: An Introduction to Methods: An Introduction to Methods 186

  • M. S. Hämäläinen, F. H. Lin, J. C. Mosher
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