[Eeglablist] filters, ICA and erp
Rey Ramirez
rrramir at uw.edu
Thu Oct 13 15:58:23 PDT 2011
Hi Steve and Sara,
As far as I know there's absolutely no 'technical reason' why my suggestion
wouldn't work. And actually it does work! Actually, if people have not been
doing this I'm not sure what kind of results they are getting since the two
main issues under discussion: 1) that 1 Hz high-pass filtering on ERP data
can seriously distort the ERP; and 2) that ICA will not work so well for
data that has not been 1 Hz high-passed filtered, are indeed quite
uncontroversial. David's suggestion (hi David!), pretty much does something
similar but detrending via DC offsetting.
There are of course BSS algorithms that work in the frequency domain (e.g.,
complex infomax, or better Independent Vector Analysis (IVA)), that could be
used to study activity at specific frequency bands, including the slow
oscillation (<1 Hz), but that's an overkill, and for simple ERP analysis
just running the ICA on the 1 Hz data, and applying the decomposition to the
0.1 Hz data is much more practical and it's what I would recommend, that is,
if you want to bother doing ICA analysis at all.
Rey
On Thu, Oct 13, 2011 at 9:09 AM, Steve Luck <sjluck at ucdavis.edu> wrote:
> Hi Sara. Unless you care about frequencies per se, epoching and
> baseline-correcting the data won't be a problem. From a time-domain
> perspective, this won't change anything.
>
> 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
>
> ps- The email trail on this topic has gotten out of hand, so I deleted
> everything except the most recent message and your original message.
>
> On Oct 13, 2011, at 7:20 AM, Sara Graziadio wrote:
>
> Steve,
> actually I was refering to your book when I was writing that the filter
> would deforme/reduce the erp. But following David Groppe's suggestion would
> mean to reduce activity at different frequency all across the spectrum,
> wihtout exactly knowing which frequencies I am reducing, am I right? If I
> want to look at the psd as well as at the erps, would this analysis just be
> correct? I am always concerned about applying data modification that I
> cannot fully control..if you know what I mean...
> Thank you very much
> Best
>
> Sara
>
>
> On Wed, Oct 5, 2011 at 10:46 AM, Sara Graziadio
> <sara.graziadio at newcastle.ac.uk> wrote:
> Hello,
> I would like just a suggestion about some data cleaning/analysis I am
> doing. I
> am doing an ERP analysis and I want to clean my data first with the ICA. In
> theory, though, I should not use an high-pass cutoff higher than 0.1 Hz to
> not
> reduce the erp amplitude. On the other side the ICA does not work well if
> the
> high-pass cutoff is lower than 0.5 Hz...what is then the best method to
> apply?
> Has anybody tested how robust the ica is with a 0.1Hz filter?
> I have also another question: I am doing the analysis on 94 electrodes
> referenced to Fz. I planned to average reference the data but actually
> there is
> quite a large spread of noise on all the electrodes with this method
> (muscular
> artefacts for example from the temporal electrodes). But actually almost
> all
> the papers are using the average reference so I was surprised, am I the
> only
> one having this problem of noise? Would not be better just to keep the Fz
> reference and then perhaps to average the erps for every different cortical
> area and do the analysis on these averaged erps?
>
> Thank you very much
>
> Best wishes
>
> Sara Graziadio
> Research Associate
> Newcastle University
>
>
> --------------------------------------------------------------------
> Steven J. Luck, Ph.D.
> Director, Center for Mind & Brain
> Professor, Department of Psychology
> University of California, Davis
> Room 109
> 267 Cousteau Place
> Davis, CA 95618
> (530) 297-4424
> E-Mail: sjluck at ucdavis.edu
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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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