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{{tag>faq eeg meg headmodel}} ====== Can I do combined EEG and MEG source reconstruction? ====== In principle the answer is "yes". However, it is sofar only supported by the low-level code in [[:development:forwinv]] and not by the high-level FieldTrip functions such as **[[:reference:dipolesimulation]]**, **[[:reference:dipolefitting]]** and **[[:reference:sourceanalysis]]**. Below is an example that demonstrates how forward computations can be done. Inverse source reconstructions using the low-level code should work similar, i.e. by combining the eeg and meg sensor definitions and volume conduction models into a cell array. Note that the same approach can also be used for combined EEG and ECoG, or combined MEG and ECoG, or any other data fusion. Furthermore note that the combination of volume conduction models can contain more realistically and accurate forward models than those used below. <code> %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % create a set of electrodes, randomly placed on the sphere elec = []; elec.pnt = randn(32,3); dum = sqrt(sum(elec.pnt.^2,2)); elec.pnt = elec.pnt ./ [dum dum dum]; % scale them to a unit sphere for i=1:32 elec.label{i} = sprintf('eeg%03d', i); end % create a concentric 3-sphere volume conductor for the EEG, the radius is the same as for the electrodes vol_eeg = []; vol_eeg.r = [0.88 0.92 1.00]; % radii of spheres vol_eeg.c = [1 1/80 1]; % conductivity vol_eeg.o = [0 0 0]; % center of sphere %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % create a set of magnetometers, randomly placed around the sphere grad = []; grad.pnt = randn(64,3); dum = sqrt(sum(grad.pnt.^2,2)); grad.pnt = grad.pnt ./ [dum dum dum] * 1.2; % scale them to a unit sphere and shift outward a bit grad.ori = grad.pnt ./ [dum dum dum]; % unit length for i=1:64 grad.label{i} = sprintf('meg%03d', i); end grad.tra = eye(64,64); % create a single-sphere volume conductor for the MEG vol_meg = []; vol_meg.r = 1.00; % radius of sphere vol_meg.c = 1; % conductivity vol_meg.o = [0 0 0]; % center of sphere %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % combine the EEG and MEG sensor definitions and volume conductor models % and do a forward computation combined_vol = {vol_eeg, vol_meg}; combined_sens = {elec, grad}; pos = [0 0 0.8]; mom = [1 0 0]'; [combined_vol{1}, combined_sens{1}] = prepare_vol_sens(combined_vol{1}, combined_sens{1}); [combined_vol{2}, combined_sens{2}] = prepare_vol_sens(combined_vol{2}, combined_sens{2}); leadfield = compute_leadfield(pos, combined_sens, combined_vol) * mom; whos leadfield Name Size Bytes Class Attributes leadfield 96x1 768 double figure; plot(leadfield(1:32)); title('eeg'); figure; plot(leadfield(33:end)); title('meg'); </code>