[Eeglablist] ICA running very slowly

Hiebel, Hannah (hannah.hiebel@uni-graz.at) hannah.hiebel at uni-graz.at
Thu Jan 19 00:41:19 PST 2017

Dear Alberto and Tarik,

thank you very much for your suggestions. I work on a computer with i7 3.60 GHz processor, 8 GB RAM or notebook with i7 2.5 GHz and 8GB Ram – this should be okay.
Gladly, the ICA eventually finds a solution and the IC maps look good. However, the question for me is still why does the ICA become >10 times slower after changing the pre-processing routine. I’ve continued testing and indeed the high-pass filter seems to be responsible for the differences.

In my recent routine I used the eeglab windowed sinc FIR filter with 1 Hz cut-off frequency, 1 Hz transition bandwidth, 0.001 passband ripple, Kaiser window. When I change the filter (settings) while keeping all other steps the same, I see huge differences in ICA runtime in some subjects. That is, when using a 0.1 Hz Butterworth filter instead, ICA is running fast again (< 1h for the subjects where it took > 30h before). With the eeglab basic FIR filter with 1 Hz passband edge and default settings defined by the internal heuristic (resulting in 0.5 Hz cut-off, 1 Hz trans. bandwidth) it’s also running much faster in most subjects but already takes >20h in the “problematic” cases.

This gives me the impression that the higher cut-off frequency causes the problems (or maybe stopband edge and attenuation are more decisive?).
That's very surprising as I would not have expected the filter to have such an impact and a higher cut-off is normally recommended.

I’d be very grateful if anyone could provide more insight!


Hannah Hiebel, Mag.rer.nat.
Cognitive Psychology & Neuroscience
Department of Psychology, University of Graz
Universitätsplatz 2, 8010 Graz, Austria

Von: Alberto Sainz <albertosainzc at gmail.com>
Gesendet: Mittwoch, 18. Jänner 2017 04:29
An: Hiebel, Hannah (hannah.hiebel at uni-graz.at)
Cc: eeglablist at sccn.ucsd.edu
Betreff: Re: [Eeglablist] ICA running very slowly

I would suggest to try in a different computer. I have been applying ICA in a 14 electrode 30min continuous EEG recording (around 40mb) in two different computers. 2Ghz dual core computer took 1h. 2.2Ghz i7 takes around 5 minutes.

I know your data is larger but just to say that the processor (and probably the RAM if is too small) matters a lot.

Good luck

2017-01-16 20:26 GMT+01:00 Hiebel, Hannah (hannah.hiebel at uni-graz.at<mailto:hannah.hiebel at uni-graz.at>) <hannah.hiebel at uni-graz.at<mailto:hannah.hiebel at uni-graz.at>>:

Dear all,

I am using ICA to clean my EEG data for eye-movement related artifacts. I’ve already done some testing in the past to see how certain pre-processing steps affect the quality of my decomposition (e.g. filter settings). In most cases, it took approximately 1-2 hours to run ICA for single subjects (62 channels: 59 EEG, 3 EOG channels).

Now that I run ICA on my final datasets it suddenly takes hours over hours to do only a few steps. It still works fine in some subjects but in others runica takes up to 50 hours. I observed that in some cases the weights blow up (learning rate is lowered many times); in others it starts right away without lowering the learning rate but every step takes ages.

I’ve done some troubleshooting to see if a specific pre-processing step causes this behavior but I cannot find a consistent pattern. It seems to me though that (at least in some cases) the high-pass filter played a role – can anyone explain how this is related? Could a high-pass filter potentially be too strict?

On the eeglablist I could only find discussions about rank deficiency (mostly due to using average reference) as a potential reason. I re-referenced to linked mastoids – does this also affect the rank? When I check with rank(EEG.data(:, :)) it returns 62 though, which is equal to the number of  channels. For some of the “bad” subjects I nonehteless tried without re-referencing – no improvement. Also, reducing dimensionality with pca ("pca, 61") didn’t help.

Any advice would be very much appreciated!

Many thanks in advance,


Hannah Hiebel, Mag.rer.nat.
Cognitive Psychology & Neuroscience
Department of Psychology, University of Graz
Universitätsplatz 2, 8010 Graz, Austria

Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
To unsubscribe, send an empty email to eeglablist-unsubscribe at sccn.ucsd.edu<mailto:eeglablist-unsubscribe at sccn.ucsd.edu>
For digest mode, send an email with the subject "set digest mime" to eeglablist-request at sccn.ucsd.edu<mailto:eeglablist-request at sccn.ucsd.edu>

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://sccn.ucsd.edu/pipermail/eeglablist/attachments/20170119/999dc8d8/attachment.html>

More information about the eeglablist mailing list