question about lcmv beamforming

[Floris de Lange]

Dear Fieldtrippers,

I have a question about the beamforming procedure, which I'm carrying
out in the time-domain using LCMV.
The strange thing I run into is that irrespective of what data I feed
the function, I get the same inverse solution (with sourceanalysis.m).

I first calculate the forward model and discretize it in a grid, using
these lines:
[vol,cfg]=prepare_singleshell([],segmentedmriF);
(..)
[grid]                    = prepare_leadfield(cfg);

Then, I run the source-analysis as follows:
data = {};
    for t = 1:6 % six epochs of 50 ms
      data{t} = mradata{2};
      data{t}.avg = data{t}.avg(:,(t-1)*30+1:t*30);
      data{t}.time = [1:30];

    cfg = [];
    cfg.method      = 'lcmv';
    cfg.projectnoise = 'yes';
    cfg.grid         = grid;
    cfg.vol          = vol;
    cfg.keepfilter   = 'yes';
    cfg.lambda       = 0; %1e-29;
        sourcet{t} = sourceanalysis(cfg,data{t});
end

I checked, and the data-avg fields from different time-windows are
(substantially) different from each other; while the avg.pow-values in
sourcet from different time-windows are numerically identical.

I don't understand how different data on the sensor-level can lead to
identical source-reconstructions. But when I look in
beamformer_lcmv.m, I see this line:
dipout.pow(i) = trace(filt * Cy * ctranspose(filt));
suggesting that the power at each voxel is a function only of the
spatial filter and covariance matrix? Does this make sense?

Any input very much appreciated!

Best wishes,
Floris



--
Floris de Lange
http://www.florisdelange.com

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