[Eeglablist] 2qs: ICA on ERP noise removal

[Jia Wu]

Hi everyone,
I'm doing ICA on 128 channel ERP to remove noise. I have 2 questions.
1. is there a quantified crietia to determining what components are
noise? if there isn't, do I need to visually go through all the 128
components? It is not only very time consuming but also not objective
because some components are very hard to tell whether they are noise or
not.

2. which kind of data should I apply ICA: single trial, averaged data,
or continuing data? I think using average data makes no sense in theory.
And continuing data is not actually continuing in time, because it is
only a series of connected potentials, and they are not always
successive. for example, in our experiment, we pause when we see the
brainwave is a mess. what's more, we usually group the trials by
conditions (stimuli) before analysis. in that way, trials in the same
group are very unlikely to be successive in time.

Hope I can get answers here.
Thanks!
Jia