[Eeglablist] ICA - message

Klados Manousos mklados at gmail.com
Thu Jan 28 23:51:02 PST 2010

Dear Maria Laura

The problem relies on the real dimensionality of the data. The real
independent sources are much more than the recorded electrodes, so fast-ICA
tries to exctract many sources in a single independent component. If you
consider the central limit theorem this component tends to have gaussian
distribution, which is a great problem...especially when you use algorithms
based on high order statistics

According to my opinion is better to use extended - infomax ICA (the default
ICA of EEGLAB) or if you want something faster you can use ACSOBIRO...which
is based on second order statistics and can retrieve components with
distributions close to gaussian.

I hope i helped...


2010/1/28 Blefari Maria Laura <m.blefari at sssup.it>

> Hi,
>    I'm using fastICA algorithm in order to remove
> artifact. I have 16 electrodes.
> Sometimes I got this messagge
> Component 13 did not converge in 1000 iterations.
> Too many failures to converge(6). Giving up. Adding the
> mean to the data.
> eeg_checkset:recompiuting the ICA activation matrix.
> Done.
> and then stopped.
> What happen, any idea? the signal is too noisy and it is
> not possible to perform the decomposition?
> Thanks in advance,
> Maria Laura
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Manousos A. Klados
PhD Candidate -- Research Assistant
Group of Applied Neurosciences
Lab of Medical Informatics
School of Medicine
Aristotle University of Thessaloniki
P.O. Box 323 54124 Thessaloniki Greece
Tel: +30-2310-999332
Website: http://lomiweb.med.auth.gr/gan/mklados
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