[Eeglablist] Per-trial channel interpolation and ICA?

[Marius Klug]

Hi Eric,

this is a great question and I look forward to the answer of the pros
(Jason Palmer for example, he created AMICA)! It also occurred to me that
interpolating a whole channel is rather often not necessary, but there is
not really any other option in EEGLAB. Maybe this is due to the ICA. For a
start, I would assume that the rank is still full (minus 1, if you use the
average reference), since there exist time points with the actual (as
opposed to the interpolated) data. You might want to check the rank and
then just try it out! If you do so, please report here!

Best,
Marius

2018-03-20 2:15 GMT+01:00 Eric Rawls <elrawls at email.uark.edu>:

> Hello EEGLAB-list,
>
> I understand that ICA can only be run on the number of channels present
> (and not interpolated; i.e. present as "actual" data) in a set of EEG data.
>
> This makes sense, because removing channels reduces the rank of the data.
> However, what effect does interpolating channels which are bad in single
> trials have on data rank?
>
> I've become curious about this because various methods (FASTER, EGI
> proprietary software, others) offer this functionality, and I'm not sure if
> it is feasible to move forward from a dataset that has been processed this
> way to an IC-based analysis.
>
> So, if a channel is interpolated on an as-needed basis rather than being
> "bad" the entire recording, how does this influence the rank of the EEG?
> What if half of the channels of a  dataset were interpolated, but in
> separate epochs?
>
> Can we move forward from this sort of artifacting schema to an analysis in
> IC-space, or does the manner of data processing preclude "knowing" the rank
> of the data and therefore an accurate IC decomposition?
>
> Thanks in advance for discussion,
> Eric Rawls, M.S.
> Graduate Research Assistant
> Department of Psychological Sciences
> University of Arkansas
>
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