[Eeglablist] Question about preprocessing EOG channels for ICA

[Ayaka Hachisuka]

Hi Makoto,

Thanks for the suggestions, and the paper!

Ayaka

On Mon, Jul 22, 2024 at 2:13 PM Makoto Miyakoshi via eeglablist <
eeglablist at sccn.ucsd.edu> wrote:

> Hi Ayaka,
>
> If you find that your suggested approach works better than the standard
> approach, go ahead and use it for your publication. Why not?
>
> However, in doing so, I recommend that you show three results: (1) No
> EOG-IC removal, (2) Standard EOG-IC removal, and (3) Customized EOG-IC
> removal in your paper, either in the main text or in the Supplement. Based
> on the comparison, try to convince your reviewers and readers including
> experts. This is the only reader-friendly way to use a novel and/or
> esoteric approach, and it's better than defending your approach just by
> citing a reference paper. It is general advice that when you are in doubt
> about whether you should choose A or B in this kind of situation, always
> choose both and show the comparison, then make a choice with justification.
>
> It's for developers, but personally, I think the following approach makes a
> lot of sense.
>
> https://urldefense.com/v3/__https://www.sciencedirect.com/science/article/abs/pii/S0165027006002834__;!!Mih3wA!CGYdTKf_6977-YZtILPE0GUP_YM4M5OjxoGCnB8OKAZ6PB-cclykRcNtoh4ayIzEpsoLCg15JMLdo2Z6hFHuwZ1CXlY$
> However, the current status of their out-of-the-box application and its
> performance compared with what's available today is unknown.
>
> ICA results above 13 Hz start to show correlations among ICs, and it will
> get worse progressively as the frequency bins increase.
> But as long as you focus on ERP components at 13 Hz and below, the standard
> use of ICA, including your suggested version, is fine.
>
> Makoto
>
> On Sat, Jul 20, 2024 at 6:28 PM Ayaka Hachisuka via eeglablist <
> eeglablist at sccn.ucsd.edu> wrote:
>
> > Hello,
> >
> > I'm wondering what your thoughts are on "aggressively filtering" only the
> > EOG channels for ICA? I read this recommendation in the EEGLAB wiki (
> >
> >
> https://urldefense.com/v3/__https://eeglab.org/tutorials/06_RejectArtifacts/RunICA.html__;!!Mih3wA!HQISzYIyD-J8Zuk4m-reRqRizEexcqAumaHZbBLFjykj2A3RBjKATuJGJwNDEJi8oDDuH1q_zJsW5OJ9XG6cDw$
> > , see below) and
> > to save myself a step, I implemented a 1Hz high-pass filter for EOG
> > channels only. The EEG channels are still filtered at 0.05Hz, my original
> > parameter.
> >
> > It seems to work really well for detecting eye movement artifacts, and my
> > data visually looks better than before after ICA, but I wasn't sure if
> this
> > was a reasonable approach.
> >
> > Thanks!
> >
> > ----------from the EEGLAB wiki page ----------
> > How to deal with the aggressive high-pass filter applied before running
> ICA
> >
> > ICA decompositions are notably higher quality (less ambiguous components)
> > when the data is high-pass filtered above 1 Hz or sometimes even 2 Hz.
> > High-pass filtering is the easiest solution to fix bad quality ICA
> > decompositions. However, for processing EEG data (such as ERP analysis),
> > high-pass filtering at 2 Hz might not be optimal as it might remove
> > essential data features. In this case, we believe an optimal strategy is
> > to:
> >
> >    1. Start with an unfiltered (or minimally filtered) dataset (dataset
> 1)
> >    2. Filter the data at 1Hz or 2Hz to obtain dataset 2
> >    3. Run ICA on dataset 2
> >    4. Apply the resulting ICA weights to dataset 1. To copy ICA weights
> and
> >    sphere information from dataset 1 to 2: First, call the Edit → Dataset
> >    info menu item for dataset 1. Then enter *ALLEEG(2).icaweights* in the
> > *ICA
> >    weight array …* edit box, *ALLEEG(2).icasphere* in the *ICA sphere
> array
> >    …* edit box, and press *Ok*.
> >
> > ICA components can be considered as spatial filters, and it is perfectly
> > valid to use these spatial filters on the original unfiltered data. The
> > only limitation is that since strong artifacts affect low-frequency bands
> > filtered out before using ICA, they may not be removed by ICA. In
> practice,
> > we have never found this to be a problem because artifactual processes
> that
> > contaminate the data below 2 Hz also tend to contaminate the data above 2
> > Hz.
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