Speaker Deck

Automated regularization of M/EEG sensor covariance using cross- validation.

by Denis A. Engemann

Published December 31, 2014 in Science

A new method for optimal regularization of MEG and EEG noise covariance estimates, implemented in Python

Based on: Engemann, D.A., Gramfort, A. (2014). Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals. NeuroImage, ISSN 1053-8119
(http://www.sciencedirect.com/science/article/pii/S1053811914010325)

and

the oral presentation titled "Automated model selection for covariance estimation and spatial whitening of M/EEG signals" held by D. Engemann at the OHBM 2014 meeting, Hamburg, Germany

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