[Eeglablist] Re-referencing/rank/ICA

[Delorme, Arnaud]

Dear Ivonne,

> With regard to re-referencing: if I recorded the data with an online average reference and then re-reference to averaged mastoids offline, I don't really understand why I woud need to add an additional channel in this case? Actually, re-referencing should not affect rank at all in this case or should it?

It depends on the type of referencing. Computing average reference will affect the rank (now the sum of all channel is 0 at all time points so the last channel is linearly dependent on all the others and the rank has been decreased by 1) unless you add back the original reference. See this section of the tutorial

https://sccn.ucsd.edu/wiki/I.4:_Preprocessing_Tools#Re-referencing_the_data

Arno

> Thanks again and best,
> 
> Ivonne
> 
> Am 02/07/2020 um 22:20 schrieb Makoto Miyakoshi:
>> Dear Ivonne,
>> 
>> The smallest eigenvalue of 10^-20 is still regarded as 'independent' in
>> terms of rank() but for practical application of ICA the algorithm may
>> behave as if rank-deficiency is present. I believe I discussed this issue
>> with Jason Palmer last time. Isn't the current 'heuristic' minimum
>> eigenvalue cutoff something like 10^-8? You should be able to find it in
>> runica() function, if I remember correctly.
>> 
>> If you can specify data rank by using the pca option, that would be the
>> best to avoid this kind of problems.
>> 
>> So what you described seems correct, except
>> 
>>>  (deficient by 1 due to re-referencing)
>> A proper re-referencing should not reduce rank. See below.
>> https://sccn.ucsd.edu/wiki/Makoto's_preprocessing_pipeline#Why_should_we_add_zero-filled_channel_before_average_referencing.3F_.2803.2F04.2F2020_Updated.29
>> 
>> 
>> Makoto
>> 
>> On Tue, Jun 30, 2020 at 3:14 AM Ivonne Weyers <
>> ivonne.weyers at uni-osnabrueck.de> wrote:
>> 
>>> Dear all,
>>> 
>>> I have a question regarding rank computation before ICA. So far, I have
>>> been using the built in MATLAB function rank(), but it has now returned
>>> weird results (as has been talked about here
>>> <https://sccn.ucsd.edu/pipermail/eeglablist/2012/004670.html>), which is
>>> why I would simply like to specify rank individually for each data set
>>> in the pca option. I would greatly appreciate it if someone could
>>> confirm my following reasoning for the rank adjustment.
>>> 
>>> My data have been recorded from 28 channels with average reference, 27
>>> of which will enter the ICA (the monopolar EOG channel is excluded- yes,
>>> I could also include it). The 27 channels have been re-ferenced to
>>> average mastoids (TP9, TP10- is it correct to include these in the ICA
>>> at all?). For some subjects, a maximum of two channels have been
>>> interpolated.
>>> 
>>> So my question is: if 27 channels enter the ICA, rank would be 26 for
>>> datasets without any interpolated channels (deficient by 1 due to
>>> re-referencing) and 26 - (number of interpolated channels) for those
>>> with interpolations?
>>> 
>>> Thank you & best,
>>> 
>>> Ivonne
>>> 
>>> --
>>> Ivonne Weyers, M.A.
>>> Research Group Psycho- and Neurolinguistics
>>> Institute of Cognitive Science
>>> University of Osnabrück
>>> Room 50/104
>>> Wachsbleiche 27
>>> 49090 Osnabrück
>>> Germany
>>> 
>>> Phone: +49 (0) 541-969-2247
>>> e-mail: ivonne.weyers at uni-osnabrueck.de
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> -- 
> Ivonne Weyers, M.A.
> Research Group Psycho- and Neurolinguistics
> Institute of Cognitive Science
> University of Osnabrück
> Room 50/104
> Wachsbleiche 27
> 49090 Osnabrück
> Germany
> 
> Phone: +49 (0) 541-969-2247
> e-mail: ivonne.weyers at uni-osnabrueck.de
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