Dear all,

I am conducting the source estimation based on the resting state EEG and have some issues I am not very sure about:

( Assuming that we only have 5-min resting state EEG data and may want to use the 'Minimum norm imaging' method to reconstruct the source)

- Just as mentioned in the tutorial, it's troublesome for calculating the Noise Covariance Matrix for resting state EEG. In this case, which strategy I should choose? Using the identity matrix or other better choices. I am not very confident about that noise is homoskedastic, and equivalent on all sensors.
- When computing sources, we have two strategies <1> right-click on the data recordings and select 'Compute sources' <2> right-click on the head model and select 'Compute sources' (something like 'shared inverse model'). I wonder these two are equivalent or any differences between them? If any difference, which one is more suitable?
- From the tutorial, I observed that we always compute the sources based on the averaged recording (average across all epochs) and want to know whether it is ok to compute the sources based on the whole recordings? I guess this may be related to the linearity of MN.

I may have some technical mistakes when understanding source estimation and please point out.

Looking forward to any help and thanks in advance.