[FieldTrip] ICA+frqanalysis questions

Stefan Debener stefan.debener at uni-oldenburg.de
Tue May 24 09:11:16 CEST 2011

Hi Odelia,

I have a slightly different opinion here. It is certainly true that any 
filter has the tendency to distort data (with distortion I mean that 
data consists of a mixture of some wanted, true signal and some unwanted 
signal, and that the removal of the unwanted part of the signal is 
neither complete nor specific). In our lab we regularly use ICA for 
artefact removal (and more), and the benefit/gain is clearly are much 
larger than the distortion. In fact there are a number of examples out 
showing that currently only ICA (or related tools) can recover the study 
of (a substantial fraction of the wanted) EEG signal (but again, it is 
NOT a perfect tool at all), in particular in cases where other means of 
SNR enhancement don't work well (averaging, spectral analysis). I am 
happy to provide references if you are interested...

For the evaluation of outcome it would be reasonable to not evaluate the 
ERP alone, as this could be misleading. Better evaluate the sensitivity 
and specificity of an eye blink attentuation approach on the single 
trial (and single subject) level, this will give you good insight. And 
it is worth keeping in mind that the preprocessing of the data (among 
other issues, like the quality of the recording and so on) largely 
determines the quality of the output (for some introduction you may look 
up chapter 3.1 in Ullsperger & Debener, 2010, Simultaneous EEG and FMRI, 
Oxford University Press). Just by a different preprocessing ICA output 
could vary between crap and excellent unmixing. Thus a poor ICA eye 
blink attenuation would make me a bit suspicious...


Am 5/24/11 4:00 AM, schrieb Alexander J. Shackman:
> And for a related perspective, see
> McMenamin, B. W., *Shackman, A. J.*, Greischar, L. L. & Davidson, R. 
> J. (2011). Electromyogenic artifacts and electroencephalographic 
> inferences revisited, */Neuroimage/*/, 54/, 4-9.
> http://psyphz.psych.wisc.edu/~shackman/mcmenamin_shackman_ni2011.pdf 
> <http://psyphz.psych.wisc.edu/%7Eshackman/mcmenamin_shackman_ni2011.pdf>
> On Mon, May 23, 2011 at 8:07 PM, Joseph Dien <jdien07 at mac.com 
> <mailto:jdien07 at mac.com>> wrote:
>     I agree with David's reasoning.  You may find the following
>     article to be of help as well in understanding the issues involved:
>     Dien, J., Khoe, W., & Mangun, G. R. (2007). Evaluation of PCA and
>     ICA of simulated ERPs: Promax versus Infomax rotations. /Human
>     Brain Mapping/, 28(8), 742-763.
>     Cheers!
>     Joe
>     On May 23, 2011, at 11:57 AM, David Groppe wrote:
>>     Hi Odelia,
>>       When you use ICA (or any other spatial filter) to correct for EEG
>>     artifacts, you're going to distort your data some by removing
>>     true EEG
>>     activity in addition to the artifact (for an explanation, see:
>>     http://www.cogsci.ucsd.edu/%7Edgroppe/PUBLICATIONS/GroppeCSO2008.pdf).
>>     So to minimize distortion, it would be better not to apply ICA
>>     artifact correction to artifact-free data.  However, if the frequency
>>     of the artifact differs across experimental conditions, it could
>>     confound your analysis.  For example, I suspect people blink more
>>     often to targets in an oddball experiment than standards.  Thus
>>     if you
>>     apply ICA only to blinky trials, you could find a difference between
>>     the EEG response to standards and targets that simply reflects the
>>     fact ICA removed more EEG activity in the target trials (i.e., it
>>     wouldn't reflect a true difference in neural processing).
>>          hope this helps,
>>             -David
>>     On Mon, May 23, 2011 at 1:44 AM, odelia nakar
>>     <odidodi at hotmail.com <mailto:odidodi at hotmail.com>> wrote:
>>>     Hi all,
>>>     I'm troubled by the fact that when I use ICA for blinks\eyes
>>>     movements
>>>     removal, I remove the relevant components also from trials that
>>>     do not
>>>     contain blinks\eyes movements. In order to avoid this bias we
>>>     thought to
>>>     combine the data before ICA ("data" structure) with the data
>>>     after ICA
>>>     ("dataica" structure), only in specific trials, as follows:
>>>     datall=dataica;
>>>     datall.trial=data.trial;
>>>     datall.time=data.time;
>>>     blinks=[2 4 5 8 bla bla 156];
>>>     for ind=1:length(blinks)
>>>          datall.trial{1,blinks(ind)}=dataica.trial{1,blinks(ind)};
>>>     end
>>>     To my first question: I just wanted to check that there is no
>>>     problem with
>>>     that, or any reason not to use it.
>>>     Another issue- I use motor learning task, and I'm trying to
>>>     understand what
>>>     happens through the process, in terms of power-frequency changes
>>>     through the
>>>     process. How would you recommend that I'd use the
>>>     ft_freqanalysis function?
>>>     What method to use (or what do I need to consider when choosing
>>>     the method
>>>     field)?
>>>     Thanks a lot,
>>>     Odelia.
>>>     _______________________________________________
>>>     fieldtrip mailing list
>>>     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>>>     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>     -- 
>>     David Groppe, Ph.D.
>>     Postdoctoral Researcher
>>     Kutaslab
>>     Dept. of Cognitive Science
>>     University of California, San Diego
>>     http://www.cogsci.ucsd.edu/~dgroppe/
>>     <http://www.cogsci.ucsd.edu/%7Edgroppe/>
>>     _______________________________________________
>>     fieldtrip mailing list
>>     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>>     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>     --------------------------------------------------------------------------------
>     Joseph Dien
>     E-mail: jdien07 at mac.com <mailto:jdien07 at mac.com>
>     Phone: 301-226-8848 <tel:301-226-8848>
>     Fax: 301-226-8811 <tel:301-226-8811>
>     http://homepage.mac.com/jdien07/
>     _______________________________________________
>     fieldtrip mailing list
>     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> -- 
> Alexander J. Shackman, Ph.D.
> Wisconsin Psychiatric Institute & Clinics and
> Department of Psychology
> University of Wisconsin-Madison
> 1202 West Johnson Street
> Madison, Wisconsin 53706
> Telephone: +1 (608) 358-5025
> Fax: +1 (608) 265-2875
> Email: shackman at wisc.edu <mailto:shackman at wisc.edu>
> http://psyphz.psych.wisc.edu/~shackman 
> <http://psyphz.psych.wisc.edu/%7Eshackman>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Prof. Dr. Stefan Debener
Neuropsychology	Lab
Department of Psychology
University of Oldenburg
D-26111 Oldenburg

Office: A7 0-038
Phone: +49-441-798-4271
Fax:   +49-441-798-5522
Email: stefan.debener at uni-oldenburg.de

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20110524/59ae91c1/attachment-0002.html>

More information about the fieldtrip mailing list