[Mne_analysis] compute_covariance estimations for different participants

[Dr. Denis-Alexander Engemann]

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Hi Sam,

The differences between the methods are rather subtle when you have long recordings.
I’d recommend to do at least methods=[‘empirical’, ’shrunk’] or [‘empirical’, ‘oas’] as a quick compromise and the way to go when using maxfilter for cleaning the MEG. In most cases, the regularized one will win.
Letting the algorithm decide how to regularize is better than forcing one method to all participants and should make your data more comparable, not less comparable.

Hope that helps,
Denis

> On Nov 28, 2018, at 2:41 PM, van Bijnen, Sam <sam.s.vanbijnen at jyu.fi> wrote:
> 
>         External Email - Use Caution        
> Hi,
> 
> When using compute_covariance for combined M/EEG data, is it advisable to use the same method for all participants, or should I let the cross-validation procedure pick the best method for each participant?
> 
> Thank you!
> Sam
> 
> 
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