[FieldTrip] Source reconstruction issues
Alice B
alice.bollini at yahoo.com
Thu Sep 7 10:18:22 CEST 2017
Hello everyone,
I would like to use fieldtrip for extracting source activity from specific ROIs (using the eLoreta approach).
Here is my script, there are few things I am not sure in the pipeline (marked with numbers on the right)
% eLORETA cfg = []; cfg.method = 'eloreta';cfg.grid = leadfield;cfg.headmodel = headmodel;cfg.eloreta.keepfilter = 'yes';cfg.eloreta.normalize = 'yes';cfg.eloreta.lambda = 0.05; *(1)cfg.eloreta.projectnoise = 'yes';eLO_source = ft_sourceanalysis(cfg,data);
% in the above line, "data" is the results of ft_timelockanalysis% with cfg.covariance = 'yes'; *(2)
% then I put the source positions from the MNI template% used for the sourcemodel (http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space)eLO_source.pos = template_grid.pos;iPOS = eLO_source.pos;iPOS(eLO_source.inside==0,:) = NaN; % only points inside gray matter
% Then I select ROIs (here only one for simplicity) to extract single-trial source activity:[v,I] = min(pdist2(iPOS, ROIs_mni , 'euclidean'));
% And I multiply the spatial filter for the EEG data in each trialW = eLO_source.avg.filter{I}; % filter at my ROI of interestfor tr = 1:size(data.trial,1) % loop over trials trials{tr} = W * squeeze(data.trial(tr,:,:)); *(3)end
Is this approach correct?My main questions are:
*(1) Is there a way to select the best lambda parameter (e.g., selecting the one that best approximates the activity at the EEG channels level)?
*(2) I am confused about the role of the covariance, since it doesn't seem to be used when source activity is estimated using the set of spatial filters at the single trial
*(3) Is the "trials{tr} = W * squeeze(data.trial(tr,:,:)); " approach correct to get time-series of source activity in a ROI?
Best,Alice
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