[Mne_analysis] Applying the fMRI weighted w file on the inverse operator

[Thinh Nguyen]

Thanks for your answer,

Is there anyway to use the dSPM or sLORETA algorithm and still be able to
reliably apply the fMRI prior weighting constraints?
Because it seems to me that, with fMRI constraints, WMNE algorithm performs
well with reasonable, as expected results, but after the noise
normalization steps (dSPM/sLORETA), the results become unexpected, if not
inaccurate.
Thank you MNE users

Thinh Nguyen


On Thu, Jun 26, 2014 at 10:01 AM, Alexandre Gramfort <
alexandre.gramfort at telecom-paristech.fr> wrote:

> hi Thinh,
>
> real quick and hand waving:
>
> dSPM / sLORETA use scaling to downweight locations
> where the noise is strong / highly amplified. This amplification
> factor is proportional to the fMRI weight. So if you normalize
> by division you pretty much cancel the main effect of the fMRI weight.
>
> HTH
> Alex
>
>
>
> On Wed, Jun 25, 2014 at 10:42 PM, Thinh Nguyen
> <thinhnguyen0405 at gmail.com> wrote:
> > Hi MNE users,
> >
> > I'm currently trying to applying a a prior source constraints via the
> fMRI
> > weighting file. But according to MNE documentation:
> >  "It turns out that the fMRI weighting has a strong influence on the MNE
> but
> > the noise-normalized estimates are much less affected by it."
> > (http://martinos.org/mne/stable/manual/mne.html#cbbdijhi)
> > Can anyone please explain to me why this is such a case, maybe in both
> > mathematical and intuitive sense. Thank you very much in advance.
> >
> > Regards,
> > Thinh Nguyen
> > Research Assistant
> > University of Houston - Biomedical Engineering department
> >
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