[FieldTrip] beamforming with rank deficient covariance matrix

[Frederic Roux]

Dear all,

I have a question related to the rank of the covariance matrix
used for the beamformer.

I preprocessed my data using ICA to reject EOG and ECG component (typically
between 2-4 components). This however, leads to a reduction in the rank
of the covariance matrix and I get a warning using ft_sourceanalysis
saying that my covariance matrix is rank deficient because rank(COV) < Nchannels.

I would like to know, how much of a problem and how serious this can be.

The way I understand things, this should only cause trouble if the number
of active sources exceeds the number of linearly independent rows of the covariance matrix?
Is this assumption correct? 

Is there some step in the ft_sourceanalyis pipeline that assumes that the number of
sources is equal to the number of channels, and that could bias the computation
of the beamformer? I mean in that case I would have more sources than channels
and thus the beamformer would fail.

Would be great if someone could help me to figure this out.

Cheers,
Fred




-- 
Frédéric Roux, PhD student
Department of Neurophysiology
Max Planck Institute for Brain Research
D-60529 Frankfurt am Main
Frederic.Roux at brain.mpg.de
+49(0)69630183225


 		 	   		  
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