[Eeglablist] filters, ICA and erp

[Rey Ramirez]

Javier,
I would not recommend doing what you suggested. Alpha is extremely important
and you should not remove it. Idle rhythms of the brain like alpha and mu
are partially phase reset by stimuli, and this is in part what produces
ERPs/ERFs. I think you are assuming a purely amplitude modulation theory for
the generation of ERP/ERF, and even if that was in part true for some
systems (e.g., auditory, since Tau rhythm is often absent in subjects), if
you filter out 10Hz, you will not get the peaks at 100, 200, 300, etc, and
completely destroy your data.
Let's be clear the reason why ICA comes up better after 1Hz high pass
filtering is that the very slow waves (<1Hz) seem to make all IC more
dependent (i.e., they all go up and down together). That's not true for
alpha.
In any case, you can always do complex infomax ICA for single frequencies or
Independent Vector Analysis for for spectral bands.
Hope this makes some sense,
Ret


On Thu, Oct 13, 2011 at 2:59 PM, Javier Lopez-Calderon <javlopez at uc.cl>wrote:

> If this would be true then this would certainly be a good way to remove
> alpha activity from bored subjects' EEG, for instance. We'd just need to
> band-pass filter the data between 8-12 Hz, run ICA, and do the trick with
> the unfiltered data...
>
> There should be something wrong with this rationale...right?
>
> Javier
>
>
>
> >
> > BTW, someone else suggested using the 1-Hz high-pass cutoff, performing
> ICA, and then applying the component coefficients to the unfiltered data.
>  That sounds like a great suggestion, although I don't know if there is a
> technical reason why it wouldn't work.  Does anyone out there know if there
> would be a problem with this?
> >
> > Steve
>
>
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-- 
Rey R. Ramírez, Ph.D.
MEG Brain Imaging Center
Institute for Learning & Brain Sciences
Portage Bay Building
Box 357988
University of Washington
Seattle, WA 98195-7988
e-mail: rrramir at uw.edu
Tel: (206) 543-6484
Fax: (206) 221-6472
Cell: (619) 709-3590
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