[Eeglablist] Per-trial channel interpolation and ICA?

[Eric Rawls]

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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