[Eeglablist] backprojection after pca

[Ralf Schmaelzle]

Hi,
I am still in the process of working into EEGLAB and was trying to get familiar with the ICA-variables. Especially I wanted to recover the original data by multiplying the source activations with the mixing matrix. As far as I understand things this should be 

   test = EEG.icawinv * EEG.icaact;
   comp = test - EEG.data                  %should be roughly zeros 

With a 256/257 channel dataset and a ICA decomposition into 256 components this seems to work. 

My question refers to the case when I - as I use to do in practice - first reduce the dimensionality using pca. Then the results of " test = EEG.icawinv * EEG.icaact" cannot be equal to EEG.data. Well, I got a bit confused about all the ICA variables (icaweights, icawinv, icasphere) and the reduction/expansion of dimensionality with pca. How can I backproject the ica-source-activities from the commandline when pca was done? 

The reason for doing this was that for testing purposes I wanted to backproject single components to the scalp and visualize them side by side in movies. I wanted to do this by zeroing out all but one row of the EEG.icaact and then project this single activity to the scalp and plot it. Is that correct?

Many thanks and my best wishes

Ralf.

P.S.:  i wonder why it seems to work with the 256/257 dataset, since EEGLAB states during the ICA process that here too the dimensionality is reduced by pca to 256 since the data are in average reference (after referencing from cz-ref) and therefore have only rank 256 but 257 channels. or is that a different case?
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