[Eeglablist] ICA vs. regression-based artifact correction effects on sensor level phase

[Manousos Klados]

Dear Baris,

Check this out-->
http://www.sciencedirect.com/science/article/pii/S1746809411000061

REGICA is a hybrid method combining the ICA with the regression-based
techniques, dealing with the known problems of both methodologies...

If you search the EEGLAB site you can find the REGICA plugin...

Best Regards

Manousos Klados

2012/2/16 Baris Demiral <demiral.007 at googlemail.com>

> Hi,
>
> Here are the questions:
>
> a) If we take out artifactual ICs (say, eye blinks), do the final
> sensor data loose their crucial phase information?
> b) If we apply linear regression based algorithms to exclude
> artifacts, will this influence the sensor level phase information?
> c) How do these two methods influence sensor based connectivity analysis?
> d) Which sensor-based connectivity measures are robust against volume
> conduction?
>
> I favor source- and ICA-based multivariate connectivity analyses where
> you really do not need to take out ICs, but work on the components of
> interest.
> But, there are plenty of papers out there reporting only pairwise
> sensor connectivity while ignoring the effects of volume conduction
> and artifact correction.
>
> Thanks,
> Baris
> --
> Ş. Barış Demiral, PhD.
> Department of Psychiatry
> Washington University
> School of Medicine
> 660 S. Euclid Avenue
> Box 8134
> Saint Louis, MO 63110
> Phone: +1 (314) 747 1603
>
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-- 
Manousos A. Klados
________________________________________________
B.Sc Mathematics
M.Sc Medical Informatics
________________________________________________
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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