[FieldTrip] Source reconstruction for time-locked EEG data at the group level

Agnese Zazio agnese.zazio at hotmail.it
Tue Jan 15 16:36:17 CET 2019

Dear all,

I'm interested in identifying sources of the EEG evoked components I get in the grand average, and I'm not going to apply further statistical analyses on sources.
I followed the Fieldtrip tutorial for source reconstruction of MEG event-related fields (http://www.fieldtriptoolbox.org/tutorial/minimumnormestimate/), which is on data from a single subject, and I'm not sure about how to proceed at the group level.

I concatenated all trials from all subjects to calculate the covariance and computing the grand average with "ft_timelockanalysis".
First, is this an appropriate way to apply mne method in "ft_sourceanalysis" at the group level?

Moreover, I was looking for a good way to check the results I obtained, for example by applying another method, such as beamformer. Is it reasonable to think that the two methods would lead to comparable results on time-locked data?
If yes, how can I apply the beamformer method in "ft_sourceanalysis"? I replaced the cfg.method field (mne with lcmv), but the output I get does not contain information about time.

Here's the code I used. I don't have individual MRIs, thus I am using templates for the headmodel (standard_bem) and the sourcemodel (cortex_5124.surf.gii).
% create a preprocessed structure
cfg =[];
cfg.channel = {'EEG'};
cfg.demean = 'yes';
cfg.baselinewindow  = [-0.1 0];
data_prepr = ft_preprocessing(cfg, data_long);

cfg =[];
cfg.covariance = 'yes';
cfg.channel ={'EEG'};
cfg.covariancewindow = [0 0.4];
data_tlck = ft_timelockanalysis (cfg, data_prepr);

% forward solution [prepare leadfield]
cfg = [];
cfg.elec = elec;
cfg.channel = {'EEG'};
cfg.headmodel = vol;   % volume conduction model
cfg.grid = ft_read_headshape('cortex_5124.surf.gii');
cfg.grid.pos = sourcemodel.pos;
cfg.grid.inside = 1:size(sourcemodel.pos,1); % all source points are inside of the brain
leadfield = ft_prepare_leadfield(cfg);

% inverse solution (method: mne)
cfg        = [];
cfg.method = 'mne'; %'lcmv';
cfg.elec = elec;
cfg.channel = {'EEG'};
cfg.grid   = leadfield;
cfg.headmodel     = vol;
cfg.mne.prewhiten = 'yes';
cfg.mne.lambda    = 3;
cfg.mne.scalesourcecov = 'yes';
source_bial_mne      = ft_sourceanalysis(cfg, data_tlck);

bnd.pos = sourcespace.pos;
bnd.tri = sourcespace.tri;
m=source_bial_mne.avg.pow(:,124); % point in time I want to plot
figure; ft_plot_mesh(bnd, 'vertexcolor', m);

Any help would be really appreciated, thanks in advance!

Agnese Zazio, PhD Student
Cognitive Neuroscience Section,
IRCCS Saint John of God Clinical Research Centre (Brescia, Italy)

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20190115/3cf56e06/attachment-0001.html>

More information about the fieldtrip mailing list