[FieldTrip] beamforming with rank deficient covariance matrix

Stephan Moratti smoratti at psi.ucm.es
Mon Mar 26 16:13:00 CEST 2012

Dear Fred,

In case of reduced rank people usually do regularization specifying  a lambda value (cfg.lcmv.lambda ='5%').



El 26/03/2012, a las 14:47, Frederic Roux escribió:

> 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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Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)


Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)

email: smoratti at psi.ucm.es
Tel.:    +34 679219982

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