[FieldTrip] Source reconstruction and NAI

[Marc Recasens]

Dear all,

As far as I know it is possible to reconstruct the time-course of the
sources (obtained using sourceanalysis) by projecting/multiplying the
filter-weights on the data.
In my case, the specific code I am using is:

 for i=1:nvoxels(inside)

        for tr=1:ntrials


ts(tr,:)=(source.avg.ori{source.inside(i)}(1,:)*source.avg.filter{source.inside(i)}*data2{condit}.trial{tr});

        end

        datvx(i,:,:)= single_trial_time_course

end
I used a common filter with 3 different conditions, thus I think this is the
only way I have to reconstruct the activity for one of the conditions.
My Question is about how to apply the NAI normalization here. Can I just
divide the output of the source reconstruction by the projected noise of the
filter? I am tempted to do something like that

datvx(i,:,:)= single_trial_time_course ./ repmat(noise(inside),[size(ts,1),
size(ts,2)]

That is, I divide the power by the noise estimate (for each voxel) in every
trial and time-point. Could anyone tell me whether this is a correct way to
procedure? Any other workaround?


Thanks in advance!

-- 
Marc Recasens
Tel.: +34 639 24 15 98
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