[FieldTrip] eLORETA spatial filter issues

[Soren Emmanuel Wainio-Theberge]

Hello Fieldtrip community,

I am a student researcher at the University of Ottawa in the Mind, Brain
Imaging, and Neuroethics unit. I have been trying to do source-space
analysis on the Human Connectome Project MEG dataset and I had some
questions about getting virtual channels using the eLORETA method. I have
been following the tutorial here (
http://www.fieldtriptoolbox.org/tutorial/virtual_sensors/) which describes
this process for LCMV beamformers.

However, when looking at the code of ft_eloreta and doing some tests of my
own, I found that the spatial filter that I get from the eLORETA method
doesn't depend on the data - that is, if I take two subjects with the same
channels, leadfield and headmodel (but different data), the spatial filter
I get from source analysis is the same for each subject. This doesn't
happen if I use other source analysis methods, such as minimum norm
estimation.

My two questions are:
1) Should the filter really be independent of the data like this? Is this
just a difference between the two methods (eLORETA and MNE)?
2) If the independence of the filter is due to a difference between the
methods, is eLORETA suitable for the extraction of virtual channels in the
same way as described in the tutorial linked above?

Any help would be very much appreciated.

Best and thanks very much in advance,
Soren
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