[Eeglablist] Applying ICA weight matrix on another dataset

[Makoto Miyakoshi]

Dear Jason,

Would you please help him? I'm interested in this question too.

> 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?


Dear Maarten,

> 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?

This seems to be an unintended inconsistency. I reported it to Bugzilla for
you.

Makoto

2013/2/14 Maarten De Schuymer <maartendeschuymer at gmail.com>

> 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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-- 
Makoto Miyakoshi
JSPS Postdoctral Fellow for Research Abroad
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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