[Eeglablist] Why average reference for ICA?

[Makoto Miyakoshi]

Dear Andreas,

> Is there a particular reason for this? Is there anything wrong in doing
ICA on EEG referenced to a single channel?

Average referencing is to impose zero-sum assumption to channel data. ICA
result does not get affected by this, except DC differences. In other
words, if you don't apply average reference, some of your IC scalp
topographies could be all read or all blue.

Overall, I would rate the importance of average referencing before ICA not
very high. It's just a minor issue even if you forgot to do so, most of
your IC scalp topos are fine. However, if you perform average referencing
after ICA, that may cause various problems so not recommended. If you
forgot to perform average reference and finished lengthy ICA process which
you can't do again for short of time, just forget it and proceed with what
you have.

> my idea was to compute the ICA on 1 Hz filtered (and average referenced)
data and apply the selection of ICs to the same unfiltered (and average
referenced) data.

If you mean you copy the ICA weight matrices to do so, yes it is a common
practice.

Makoto



On Thu, Jul 26, 2018 at 2:29 AM Andreas Pedroni <andreas.pedroni at uzh.ch>
wrote:

> Dear Makoto, dear EEGLAB list
>
> I came across several sources where it is suggested to use average
> referenced data to perform ICA (including your very helpful discussion
> about preprocessing
> https://sccn.ucsd.edu/wiki/Makoto%27s_preprocessing_pipeline
> <https://sccn.ucsd.edu/wiki/Makoto's_preprocessing_pipeline>). Is there a
> particular reason for this? Is there anything wrong in doing ICA on EEG
> referenced to a single channel?
>
> In addition, I have the goal to apply ICA on (1 Hz filtered) data with the
> purpose to get rid of artifacts (using MARA), but apply the clean ICs on
> unfiltered data to keep lower frequencies than 1 Hz. Based on your
> comments, my idea was to compute the ICA on 1 Hz filtered (and average
> referenced) data and apply the selection of ICs to the same unfiltered (and
> average referenced) data. Is that the way to go, or are there other
> suggestions?
>
> Thanks and all the best
>
> Andreas
>
> Andreas Pedroni
> Psychologisches Institut
> Methoden der Plastizitätsforschung
> Andreasstrasse 15, AND 4.58
> CH-8050 Zürich
> andreas.pedroni at uzh.ch
>
>
>
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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