[Eeglablist] Applying ICA weight matrix on another dataset

[Maarten De Schuymer]

Dear list,****


I have a question concerning the role of the sphering matrix (which
decorrelates the channels) in the rather common scenario where I compute an
ICA on one version of a dataset, but then apply the ICA results to another
version of the same data (e.g. epoched vs. continuous, filtered vs.
unfiltered).

To remove artifacts in my study, I compute the ICA on high-pass filtered
(e.g. 1 Hz) data, because this results in much better ICA decompositions.
However, I would like to apply the results of this ICA to my original,
unfiltered version of the same dataset, because would like to keep slow
potentials (< 1 Hz) in the data. After running ICA on the filtered data, I
save both EEG.icaweights and EEG.icasphere.


When I now apply the ICA weight matrix to the original data it is unclear
to me which sphering matrix needs to be used.****

Should I (A) also import the ICA sphering matrix from the filtered data or
(B) recompute the sphering matrix (cmd: sphere(EEG.data)) for the original
unfiltered data and consequently use that one. Both possibilities result in
different outcomes since sphering matrices are different for both versions
of the datasets. Which of these possibilities are recommended and more
importantly, why exactly?****

A related question concerns the exporting-importing of the weight matrix in
the GUI of EEGLAB. When exporting weights, a single exported file contains
the combined weight*sphering matrix. However, when importing, two different
files need to be imported, i.e. both weight matrix and sphere matrix
separately. This does not seem practical. Or is there a rationale behind
this distinction between import and export?****


Thanks for any input on this,****


Best
Maarten De Schuymer****

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