[FieldTrip] SVD and ICA

[Federico Grande]

Hi Diego,

I'm sorry, I was probably not clear enough. When you uses SSP (Signal Space Projection), to process the rawdata, it projects the data in 8 or 10 PCA, but when you uses SSS in the rawdata, it has a much higher amount of components , around 150 or almost 200. That is the reason that makes me having no idea about how should I reduce it.

Cheers,

Federico

----- Mensaje original -----
De: "Lozano Soldevilla, D. (Diego)" <d.lozanosoldevilla at fcdonders.ru.nl>
Para: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
Enviados: Viernes, 10 de Enero 2014 18:27:17
Asunto: Re: [FieldTrip] SVD and ICA

Hi Federico,
I don't follow you. What's SSP? In any case, what I explained it's the way that I know to reduce data dimensionality prior ICA computation. I don't know a procedure to know optimal number of PCA component but here 25 were used: http://www.ncbi.nlm.nih.gov/pubmed/19699307

best,

Diego

----- Original Message -----
> From: "Federico Grande" <fgrande at cbs.mpg.de>
> To: "Diego Lozano" <d.lozanosoldevilla at fcdonders.ru.nl>, "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Friday, 10 January, 2014 6:14:28 PM
> Subject: Re: [FieldTrip] SVD and ICA
> Aham, that is what I've done, do the runica method, but I didn´t use
> the parameter pca: pca are not principal component analysis associated
> to SSP? I have used SSS (signal space separation) instead of SSP. It
> would work also? And also I don´t know what number of components do I
> want to reduce my data. How can I know which is the optimal number?
> 
> Thank you Diego,
> 
> Federico
> 
> ----- Original Message -----
> From: "Lozano Soldevilla, D. (Diego)"
> <d.lozanosoldevilla at fcdonders.ru.nl>
> To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Friday, January 10, 2014 4:13:13 PM
> Subject: Re: [FieldTrip] SVD and ICA
> 
> Hi Federico,
> 
> You might want to have a look to the different ICA algorithms
> ft_componentanalysis has and see how to choose the proper option. For
> example, if you select cfg.method='runica' then cfg.runica.pca =
> number of components you want to reduce your data.
> 
> Check help ft_componentanalysis for details
> 
> best,
> Diego
> 
> 
> ----- Original Message -----
> > From: "Federico Grande" <fgrande at cbs.mpg.de>
> > To: fieldtrip at science.ru.nl
> > Sent: Friday, 10 January, 2014 3:54:56 PM
> > Subject: [FieldTrip] SVD and ICA
> > Hello everyone,
> >
> > In order to remove the artefacts like blink eyes or hearbeat, I
> > wanted
> > to apply ICA to my data. I've been told that is better to apply
> > first
> > SVD and then ICA, but I don't really know how to apply it. What do
> > you
> > recommend me in order to do it? I've not found any tutorial for
> > doing
> > it. All help and information ins greatly welcomed.
> >
> > Thank you very much,
> >
> > King Regards,
> >
> > Federico Grande
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> --
> PhD Student
> Neuronal Oscillations Group
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> NL-6525 EN Nijmegen
> The Netherlands
> http://www.ru.nl/people/donders/lozano-soldevilla-d/
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
PhD Student
Neuronal Oscillations Group
Donders Institute for Brain, Cognition and Behaviour 
Centre for Cognitive Neuroimaging
Radboud University Nijmegen 
NL-6525 EN Nijmegen
The Netherlands
http://www.ru.nl/people/donders/lozano-soldevilla-d/

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