[Mne_analysis] Mne_analysis: dSPM

[Yury Petrov]

Dear Daniel,

I was rereading your excellent dSPM intro, and have the following  
degrees of freedom (DoF) question: what is the right number of DoF for  
the noise in the F denominator? You say the number of the "baseline"  
timepoints x 3. Where does this number of baseline timepoints come  
from? Shouldn't it be just 3 (just as for the numerator), because we  
add three variances? Also, if it was really not 3, then the correct F  
value wouldn't be simply F = signal^2/noise^2 but F = signal^2 / 3 /  
noise^2 / DoF_noise, i.e. the numerator and denominator would have to  
be normalized by their respective DoFs, right?

Thanks,
Yury

On Oct 2, 2008, at Oct 2, 2008 | 1:20 PM, Yury Petrov wrote:

> Daniel, first of all, thanks for the great MNE review. Some typos  
> that I noticed:
> page 30: remove Gaussian source distributions
> page 33: theorm -> theorem
>
> I find the MNE derivation based on Bayesian max-likelihood method  
> (e.g. in the Inverse Problem Theory book below) both simpler and  
> more satisfactory. In particular, it makes the nature of the MNE  
> assumptions much more explicit.
> http://www.ipgp.jussieu.fr/~tarantola/Files/Professional/Books/index.html
>
> I don't see what's 'not cool' with subtracting dSPMs for two  
> conditions. dSPM is, essentially, a singnal-to-noise ratio. Assuming  
> that your noise was the same in both conditions (i.e. the same noise  
> covariance matrix) we just subtract signals, right?
>
> On Oct 2, 2008, at Oct 2, 2008 | 11:49 AM, Daniel Goldenholz wrote:
>
>> Hi Alex
>>
>> For what it is worth, I thought about these kinds of questions some  
>> time ago and presented a talk that was supposed to open up further  
>> discussion and debate. The PDF of that talk is here:
>>
>> http://www.nmr.mgh.harvard.edu/~daniel/links/presentation/stats_on_roi.pdf
>>
>> It includes some basics on the mathematics and assumptions inherent  
>> in them. Then the talk veers into the speculative with some  
>> thoughts on newer possible methods for comparing conditions when  
>> you have multiple subjects and multiple conditions.
>>
>> I am still interested in developing these questions further, so let  
>> me know if these ideas are helpful.
>>
>> Daniel
>>
>>
>> On Mon, Sep 29, 2008 at 6:28 AM, Alex Clarke <alex at csl.psychol.cam.ac.uk 
>> > wrote:
>> Hi there,
>>
>> I have a question regarding how best to statistically compare two  
>> conditions. So far I have only being comparing between 2 conditions  
>> using ROIs and comparing current estimates over time. However, I'd  
>> also like to see the difference between two conditions across the  
>> whole brain. I was wondering what the best approach to this was  
>> (Ideally ending up with a dSPM map of condition1 - conditon2).
>>
>> Any help on this would be appreciated
>>
>>
>> Thanks,
>>
>> Alex Clarke
>> _______________________________________________
>> Mne_analysis mailing list
>> Mne_analysis at nmr.mgh.harvard.edu
>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>
>>
>>
>> -- 
>> Daniel Goldenholz MD, PhD
>> --------------------------------------------------------
>> http://www.nmr.mgh.harvard.edu/~daniel
>> _______________________________________________
>> Mne_analysis mailing list
>> Mne_analysis at nmr.mgh.harvard.edu
>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>