[Eeglablist] ICA - message

Blefari Maria Laura m.blefari at sssup.it
Thu Jan 28 23:59:04 PST 2010


Thanks Manousos for your clear and quick answer. I will 
try it.

Maria Laura


On Fri, 29 Jan 2010 09:51:02 +0200
  Klados Manousos <mklados at gmail.com> wrote:
>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...
>
>Manousos
>
>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
>Fax:+30-2310-999263
>Website: http://lomiweb.med.auth.gr/gan/mklados



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