Summary
I need to remove artifact that appears strongly on all channels in my EEG data. It's already recorded (from another lab) so I can't use hardware solutions. Also: band overlap and no reference channel.
Less Short
I have 28 EEG channels with strong common-mode artifact (artifact amplitude is on the order of $10^4$, the rest is on the order of $10^2$), but I don't have a channel I can specifically call a reference channel. If you run cross-correlation between the channels, all pairs have a $C_{xy}>0.98$, all at 0s lag. That alone tells me it's artifact.
Is there a standard practice for removing this kind of artifact from signal? Artifact band overlaps signal band, so band-pass filters aren't enough. I thought to call one channel the reference channel and subtract it from all others, but then I either have to manually pick a ref channel for each file (many files), or rely on a given channel being well-behaved (not all are). An option I like more is to take the mean at each time step, and subtract it from each channel. In Matlab code, artifact_free = raw_data - mean(raw_data,2) (columns = channels, rows = time steps).
The second option implicitly assumes that non-artifact components can be characterized as random, independent processes, and could smooth/remove cortical response in the signal that happens at/near the same time on different channels. Because of this I'm still a bit uncomfortable with doing that. I'm a little new to EEG so I don't know what assumptions I'm allowed to make. We got the data from another lab, so there are no EEG experts to ask here, and I don't want to lose information in the data or do something that statistics says I can't.
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