[Eeglablist] Question about preprocessing EOG channels for ICA

[Ayaka Hachisuka]

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.