[Eeglablist] Can I use independent components derived from filtered data for correction of unfiltered data?

[Niko Busch]

Dear EEGLAB users,

is it reasonable to compute ICA components on a highpass filtered (0.5 
Hz) dataset, and then use the solution to correct eyeblinks in the 
unfiltered dataset?

I recently conducted a recognition memory experiment. The epochs are 
long, there are a lot of eyeblinks, and, unfortunately, a lot of slow 
electrode drifts which are probably sweat artifacts (beware of recording 
experiments in July!). I would like to use ICA to correct the eye 
artifacts, but I am afraid that the slow drifts would trouble the ICA 
solution. On the other hand, I do not want to highpass filter the data, 
either, since this also eliminates the slow potential effects I am 
interested in. Therefore, could I run ICA on the highpass filtered 
dataset, then transfer the weights to the unfiltered dataset, and 
finally use them for eyeblink correction? Or would that distort my data 
in some way?

Thank you and best regards,
Niko.

-- 
Dipl.-Psych. Niko Busch

Otto-von-Guericke-Universität Magdeburg
Institut für  Psychologie
Abteilung für Biologische Psychologie
Postfach 4120
39016 Magdeburg

Tel.: +49 (0) 391- 67 11969
Fax:  +49 (0) 391- 67 11947 

Website: www.uni-magdeburg.de/nbusch