[Mne_analysis] MNE pca and SNR

[Yury Petrov]

EEGLab, which is an extensive free Matlab package has an ICA  
extension. What you should think about is whether trying to remove eye- 
blinks, etc by using ICA is worthwhile. There is always a chance that  
it will corrupt your data. It is safer and, in my view, a better  
practice to simply collect more data and totally dump all the time  
intervals with artifacts using a simple threshold artifact detector.

On Nov 18, 2008, at Nov 18, 2008 | 7:19 AM, Daniel Goldenholz wrote:

> Marina
> 1. The snr issue is actually a very deep one. You are telling MNE  
> how to set up the regularization parameter, and yes, it will change  
> the resulting signals. The reason that happens is that there are  
> many more brain states than there are MEG sensor states. (this is  
> that "ill-posed problem" thing). As a result, we do a pragmatic  
> thing, which is simplify the problem and make it solvable - we add  
> the constraint of minimizing the current at every point in the brain  
> (loosely described). But when we do that, we need to make a somewhat  
> arbitrary choice about how much weight to give that constraint.  
> Because there is no simply physical interpretation of what we are  
> doing, physiology cannot easily guide us here. In practice, I have  
> no suggestion. I defer to Matti.
>
> 2. I did some reading on the subject of artifact removal a few years  
> ago. I haven't kept up with the literature there. But I recall  
> reading a relatively compelling argument against using PCA for  
> artifact removal that Dan hinted at. Essentially PCA does not care  
> if it also removes real brain data along with artifact. One possible  
> approach suggested out there was a related technique, called ICA. I  
> believe someone has written a matlab toolbox for that. But the  
> results there are still sometimes suspicious. If you trust SSS, that  
> may be an extremely powerful method to removal any artifact not  
> coming from the head. As for eye blinks and movements - you could  
> consider adaptive filtering. Another possibility is to fit several  
> dipoles at the anatomical location of the eyes, and fit data to  
> them, and remove them. In my playing around with these issues very  
> briefly, I didn't find one perfect solution. But many papers are out  
> there saying they did.
>
> Hope my vagaries are mildly useful
>
> Daniel Goldenholz MD, PhD
> --------------------------------------------------------
> http://www.nmr.mgh.harvard.edu/~daniel
>
>
> On Tue, Nov 18, 2008 at 6:13 AM, Daniel G. Wakeman <dgwakeman at gmail.com 
> > wrote:
> Hi Marina,
>
> 1.  I think the lack of reply generally reflects people's tendency  
> to leave it alone.  Please people chime in, if I'm wrong.
>
> 2.  There is no function in MNE that does a PCA.  The closest thing  
> within MNE would be the ability of mne_browse_raw to create SSP  
> projections.  However, I would not recommend using this for that  
> purpose; again please chime in, if you disagree.  The next best  
> possibility to work on this would be to use the excellent MATLAB  
> toolbox to read the fif files into matlab remove the eyeblinks/ 
> cardiovascular artifacts using whatever technique you like best and  
> save the data back and continue processing.  Just be very careful  
> with your noise covariance matrices and your artifact extraction as  
> many of these tools have dangerous consequences for the true brain  
> data.
>
> Dan
>
>
>
> On 7 Nov 2008, at 13:39, Marina Papoutsi wrote:
>
>>
>> Dear MNE users,
>>
>> I have two questions that I hope someone can answer.
>>
>> 1) The first is about SNR. Following an older post that I made on  
>> SNR (left unaswered :-( ) I will attempt to rephrase the question,  
>> hoping to hear back from someone.
>>
>> I am still wondering about how to best use the option --snr in  
>> mne_make_movie. I have played around with the data a bit and  
>> changing the SNR value seems to make a difference in the stc files.
>>
>> So what is the best way to chose an SNR?
>> a) use the default value (3) independent of whether this is  
>> reflected in your data
>> b) estimate the mean SNR value (over the epoch time), which will be  
>> different for each subject and condition?
>>
>> At the moment, I have calculated the SNR for each subject and  
>> condition. The SNR value is between 1 and 2 and it is different for  
>> subjects and conditions. Will that be a problem when I need to do  
>> group-level statistics comparing different conditions?
>>
>> 2) The second question is about PCA. Is there any function in MNE  
>> that would allow one to do a PCA on the *.fif files to remove eye- 
>> blinks or cardiovascular related oscillations?
>>
>> Thank you in advance for the help,
>> Marina
>>
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>
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