[Eeglablist] Applying ICA weight matrix on another dataset

[Arnaud Delorme]

I think it is an interesting question.
I would like to see what Jason thinks of it.

To summarize it for Jason

Two EEG dataset (let say from the same subject and the same session)
- EEG dataset 1 -> sphering 1 and weight matrix 1
- EEG dataset 2 -> sphering 2

Now, for EEG dataset 2, if we want to reuse the ICA solution of dataset 1, wouldn't it be better to use "sphering 2 and weight matrix 1" instead of "sphering 1 and weight matrix 1". Obviously since it is the same subject and same session sphering 1 and 2 should be almost identical?

Maybe it is actually an experimental question that could be answered using the getMIR function?

Thanks,

Arno

On 22 Feb 2013, at 13:40, Makoto Miyakoshi wrote:

> Dear Maarten,
> 
> I asked it to Nima offline at SCCN B177E. He said categorically no because ICA weight matrix is very dependent of the sphering matrix.
> 
> By the way you can download a function getMIR() which is included in the amica toolbox downloadable from the following URL link: http://sccn.ucsd.edu/wiki/Amica_Download 
> This function would eventually tells you which W works better in terms of mutual information reduction (this unmixing matrix W should be a product of sphering matrix x ica weight matrix). Let us know if you find something interesting.
> 
> Makoto
> 
> 2013/2/22 Maarten De Schuymer <maartendeschuymer at gmail.com>
> Dear list,
> 
> I am still trying to figure out which is the correct sphering matrix when applying ICA weights to another version of the same dataset.
> Is there an expert who can weight in on this issue?
> 
> Thanks a lot,
> Maarten De Schuymer
> 
> 
> ---------- Forwarded message ----------
> From: Maarten De Schuymer <maartendeschuymer at gmail.com>
> Date: 2013/2/14
> Subject: Applying ICA weight matrix on another dataset
> To: eeglablist at sccn.ucsd.edu
> 
> 
> 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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