[Eeglablist] Rank deficient data

[Madeline Anne Gregory]

Hi all, 

I am having some issues trying to figure out how to deal with rank deficient data.

Initially, I ignored rank deficient data and ran ICA after interpolating bad channels and re-referecing to the average reference. I know this can produce 'ghost ICAs' but how problematic is it really? Especially in my case when dealing with a 256-electrode array. 

I decided that in case it really is an issue, I should try to find a way to fix it. At first, I tried interpolating and re-referencing after ICA. This is problematic because re-referencing after ICA removes all ICA weights. From what I understand, this does not 'undo' any of the removed ICs/artifacts (that were removed during ICA), so it is only really problematic if I intend to use ICs later on for analysis (someone please correct me if I am wrong). At this point, I am unsure whether I will need the ICs (I may just use channels instead), but I don't want to be in a situation where I'd like to do an analysis that requires them but I'm unable to. 

I then tried to use the pca option for runica in order to run ICA only on non-interpolated channels (i.e. only on 'real' data). However, when I then try and run ADJUST after ICA, I get the following error message:

If ICA was not run on all channels, remove the excluded channels before running ADJUST.
They can be reintroduced by interpolating them from neighbour channels after artifact removal.

As I previously mentioned, I don't want to interpolate after ICA. So I went into the ADJUST code and removed the line which specified that number of ICs must = number of channels. I was able to run ADJUST just fine after that, however I suspect I probably changed something pretty important about the algorithm..

I know I could just not use an algorithm to reject ICs and instead reject ICs myself, however I am not keen to do this for up to 256 ICs... I also think using the algorithm makes the process a little bit more objective. 

At this point, I'm inclined just to ignore the rank deficiency issue... but of course I don't want this to negatively affect my results or lead to erroneous conclusions. For reference, I intend to use this data for time-frequency analysis. 

I appreciate any suggestions or comments!

Thank you,
Maddie