[FieldTrip] Deviations in Inverse Solutions between Fieldtrip and MNE-C packages?

[Schoffelen, J.M. (Jan Mathijs)]

Dear Burkhard,

I don’t know about the unexpected eLoreta results (this code has been contributed by Guido Nolte), but in general I suspect that MNE-C has some clever tricks up its sleeve to deal with the different channel types / rank deficiency of the data, which is something you need to account for explicitly in FieldTrip. I don’t know why sLoreta would be more robust against this, but that’s how it is.

For now, I suggest to follow the suggestions in the minimumnormestimate tutorial website, where recommendations are given for the appropriate cfg. Importantly, the default MNE is just a pinv of the leadfield matrix, which is probably not ideal. You’d want to switch on the prewhitening (this is currently still done for the MNE method in the minimumnormestimate function), as well as regularization.

Best wishes,
Jan-Mathijs


> On 15 Nov 2019, at 13:01, Burkhard Maess <maess at cbs.mpg.de> wrote:
> 
> Dear Frieldtrip experts,
> 
> since I like to use freesurfer segmentations and the nicely prepared
> coupling with MNE, I took some effort to import those volume conductors
> and source space models into fieldtrip as well. This seems to work as
> fas as it concerns the geometric representation in space (the
> coregistration - pp04a_volume_sources.png). The coregistration was made
> via MNE-C and also imported into fieldtrip. In summary, I am using the
> same model (volume conductor + source space), the same coregistration
> and the same data.
> 
> For visualization, I have attached figures made by either MNE-C or by
> matlab/fieldtrip. In general, all attached jpg-files were generated
> using MNE-C and all png-files were produced by matlab/fieldtrip.
> Attached figs can be downloaded from this file share:
> https://owncloud.gwdg.de/index.php/s/19WpPrV5Dw0gD28
> 
> Using sloreta as the inverse method, there is also a reasonable match
> between both packages of software. Please check the attached files
> pp04a_sloreta_90ms*.{jpg,png} .
> 
> However, what is when using a different method, e.g. minimum norm
> estimates? Please see the corresponding pics: pp04a_mne_90ms*.{jpg,png}.
> The MNE solution estimated via MNE-C is similar to the sloreta solution.
> Fieldtrip, however, estimates something completely different. The MNE
> solution by fieldtrip rather appears to have some meshing problem, or
> so? The same pattern can also be observed for different subjects' data.
> Fieltrip also offers eloreta as a method - again a different solution,
> but also very unexpected (no figs attached, though).
> 
> What could be possible reasons for this unexpected behaviour?
> 
> Regularization? Covariance matrices? Here is the relevant part in my
> matlab script which switches between the methods. Which options do I
> need to activate in case of the 'mne'-method or the 'eloreta' method -
> both deviating strongly from the expected solution.
> 
> %% Source localization using different methods
> % sourcemethod      = 'sloreta';
> % sourcemethod      = 'eloreta';
> sourcemethod      = 'mne';
> cfg               = [];
> cfg.method        = sourcemethod;
> cfg.grid          = leadfield;
> cfg.headmodel     = headmodel;
> cfg.latency       = 'all';
> cfg.mne.lambda      = 0.03;
> cfg.eloreta.lambda  = 0.03;
> cfg.sloreta.lambda  = 0.03;
> source            = ft_sourceanalysis(cfg, tl);
> 
> If needed, I could share all data files needed to run the same analysis
> on your computer.
> 
> Hints would be much appriciated - thank you very much in advance,
> 
> all the best,
> 
> Burkhard
> 
> 
> 
> 
> 
> 
> -- 
> Dr. Burkhard Maess
> Brain Networks (@brainnetleipzig)
> Max Planck Institute for Human Cognitive and Brain Sciences
> Stephanstr. 1a, D-04301 Leipzig, Germany
> phone/fax: +49 341 9940-2526/-2511   mail: maess 'at' cbs.mpg.de,   http://www.cbs.mpg.de
> 
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> https://doi.org/10.1371/journal.pcbi.1002202