[FieldTrip] Source reconstruction on BEM mesh of EEG data

[Arnaud Delorme]

Thank you Jan,

The BEM is a volume conduction model, and describes the geometries at which the potential distributions are computed that are the consequence of the volume currents, due to the primary currents in the brain.

Yes, I thought the 3-D volume defined the position of the dipoles. I was confused by the fact that even though the BEM model is defined by surfaces, it requires to compute a volume conduction model.

Anyway, I have built a tutorial for people using EEGLAB so they could use their EEGLAB datasets to perform source localization in Fieldtrip using either a volumetric or a surface MNI template source model.

https://sccn.ucsd.edu/wiki/A08:_DIPFIT#Advanced_source_reconstruction_using_DIPFIT.2FFieldtrip

As you could tell I am not well versed in the subtleties of source reconstruction. Feel free point to any potential error or inaccuracy. In particular, when I used minimum norm estimation on P300 data, the solution leads to extremes values on some of the vertices. I am not sure if it is a good sign (the solution is very focal), or a bad sign (values blew up). I am caping the values for visualization purposes (which is equivalent to changing the color scale) because the max is likely within a sulcus and not visible.

cfg               = [];
cfg.method        = 'mne';
cfg.grid          = leadfield;
cfg.headmodel     = headmodel.vol;
cfg.mne.lambda    = 3;
cfg.mne.scalesourcecov = 'yes';
source            = ft_sourceanalysis(cfg,dataAvg);
m=source.avg.pow(:,180); % plotting the result at 400 ms
m(m>100) = 100; % clip extreme values
figure; ft_plot_mesh(source, 'vertexcolor', m);
view([230 0]); h = light; set(h, 'position', [0 1 0.2]); lighting gouraud; material dull

Leads to this figure https://sccn.ucsd.edu/wiki/File:Fieldtrip_surface_solution.png

Is there a regularization parameter for the MNE method that could be tuned? I could not find any documentation on that. Anyway, if anybody can comment on that behavior, I would greatly appreciate.

Best wishes,

Arno


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https://doi.org/10.1371/journal.pcbi.1002202