[FieldTrip] ICA+frqanalysis questions
jdien07 at mac.com
Fri May 27 05:16:03 CEST 2011
Stefan, just to be clear, I don't think any of us were saying not to use ICA to correct blinks. David was just saying that there are potential concerns when one only applies the ICA to the blink trials rather than to all the trials. I myself use EEGlab's infomax implementation in the automatic eyeblink correction tool of my EP Toolkit (http://sourceforge.net/projects/erppcatoolkit/).
Now that said, I should add a little more nuance to my response. One of the things I observed (or rather, that Tim Curran pointed out to me) is that when you apply ICA to remove eyeblink artifacts in this manner, it can actually substantially increase the noise level in the data, so for the trials without eyeblinks it can have a considerable cost. So in order to balance the cost/benefit ratio, what I did was to include a trial by trial criterion that the putative eyeblink factors would only be removed if doing so reduced the overall variance of the trial. This approach does still have some potential for causing the concerns that David raises but not as much as only applying the ICA to blink trials since it does end up getting applied to non-blink trials too. This does mean that one should be cautious about any apparent effects in the artifact corrected data that are centered around the eyes (that have a blink topography) but that goes without saying in any case. So anyway, I agree, it's not perfect but seems to be the best available option.
On May 24, 2011, at 3:11 AM, Stefan Debener wrote:
> 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.
>> On Mon, May 23, 2011 at 8:07 PM, Joseph Dien <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.
>> 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:
>>> 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,
>>> On Mon, May 23, 2011 at 1:44 AM, odelia nakar <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:
>>>> blinks=[2 4 5 8 bla bla 156];
>>>> for ind=1:length(blinks)
>>>> 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
>>>> Thanks a lot,
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>> David Groppe, Ph.D.
>>> Postdoctoral Researcher
>>> Dept. of Cognitive Science
>>> University of California, San Diego
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>> Joseph Dien
>> E-mail: jdien07 at mac.com
>> Phone: 301-226-8848
>> Fax: 301-226-8811
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> 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
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
> 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
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