[Mne_analysis] group dSPM?

[Elena Orekhova]

Dear Alex,  Hari

Do you think it is possible to estimate significance of the group mean dSPM values?
In case of loose constrains the dSPM values come from F distribution with dof 3 and Npoints x 3 (Dale, 2000). One can e.g. calculate distribution of the means of N (N=number of subjects) randomly generated F values and empirically assess what value would correspond to e.g. p=0.05.

Elena

________________________________________
From: Alexandre Gramfort [gramfort at nmr.mgh.harvard.edu]
Sent: Friday, June 08, 2012 10:26 PM
To: Hari Bharadwaj
Cc: Elena Orekhova; mne_analysis at nmr.mgh.harvard.edu; Tatiana Stroganova
Subject: Re: [Mne_analysis] group dSPM?

if the noise normalization is different for the 3 orientations you
cancel the effect
of the fixed or loose orientation and end up with solutions that look very much
like free orientation solutions.

Alex

On Fri, Jun 8, 2012 at 7:12 PM, Hari Bharadwaj <hari at nmr.mgh.harvard.edu> wrote:
> Question: Why is the noise normalization the same for the 3 orientations?
> Shouldn't it depend on the 3 lead fields?
>
> Hari
>
> On Fri, June 8, 2012 12:01 pm, Alexandre Gramfort wrote:
>>>  If you combine using A = x^2 + y^2 + z^2 (i.e without the square root
>>> or
>>> square what MNE gives you) and if x,y,z are *after noise normalization*,
>>> then it is reasonable to assume that A is chi2 as long as the noise
>>> covariance was computed using a large number of points, I wouldn't be
>>> concerned about variances being different since each has approximately
>>> variance 1 in the null...
>>
>> the noise normalization is the same for x, y and z and as you regularize
>> more the tangential components than the radial I don't think the
>> variance will be
>> the same even when you apply dSPM to noise. But I should check as it's
>> just an intuition.
>>
>>> The maps we have gotten from running long permutation tests at the group
>>> level and then thresholding using this transformation look very similar.
>>> So our current practice is to use this transform and run the usual
>>> parametric analyses and invest time in running permutations as
>>> confirmation once we see something we like.
>>
>> ok. Thanks for sharing your experience.
>>
>> Alex
>>
>>
>>
>
>
> --
> Hari Bharadwaj
> PhD Candidate, Biomedical Engineering,
> Boston University
> 677 Beacon St.,
> Boston, MA 02215
>
> Martinos Center for Biomedical Imaging,
> Massachusetts General Hospital
> 149 Thirteenth Street,
> Charlestown, MA 02129
>
> hari at nmr.mgh.harvard.edu
> Ph: 734-883-5954
>
>
>
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