[Eeglablist] Re-referencing/rank/ICA

[Ivonne Weyers]

Dear Makoto,

thanks for the quick reply, I really appreciate it! I was able to fix 
the problem by adjusting the eigenvalue cutoff in the pop_runica() 
function (l.531), the original cutoff was 10^-7. I might specify rank 
via the pca option regardless, however, just to be safe (and since I am 
merely using ICA to reject eye-movement artifacts).

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?

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