[Eeglablist] ICA running very slowly

Alberto Sainz albertosainzc at gmail.com
Tue Jan 17 19:29:39 PST 2017

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