[Mne_analysis] Comparing conditions

[Yury Petrov]

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
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>
>
> -- 
> Daniel Goldenholz MD, PhD
> --------------------------------------------------------
> http://www.nmr.mgh.harvard.edu/~daniel
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