[Eeglablist] Using PCA before ICA decomposition?

[Chang Gu]

Hi all,

I'm  conducting ICA to clean my segmented EEG data.   Because the length of
my data is short, I have to use PCA option (by choosing ['pca', 35] in
EEGlab, or EEG = pop_runica(EEG,
'icatype','runica','dataset',1,'options',{'pca' 35});) before doing ICA
decomposition.

I wonder what is the number of the ranks for my data after the PCA by
EEGLAB?

For example, I have 128 channels for my recording, so without PCA, I should
have 128 ICs corresponding to 128 linear independent time-series. If I
remove some eye components (say 20 ICs) to clean the EEG, I should still
have 108 ranks of my cleaned data, and in theory I should be able to
conduct PCA 108 then  ICA recursively, by choosing ['pca', 108] in runica.

However, If I first do PCA 35 then ICA ( it returns 35 ICs) and remove 20
ICs, do I *only have 15 ranks* left or I *still have 108 ranks* for the
cleaned data? If I want to do ICA again, what number I should put in ['pca'
...]? Is the PCAed data the same as the raw data, but only with a linear
transform, or EEGlab change the data at PCA step by deleting the small PCs
and then conduct ICA on the first 35 PCs?

Thanks in advance!

-- 
Chang Gu
Psychology & Human Development
Vanderbilt University
Nashville, TN
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