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

Hari Bharadwaj hari at nmr.mgh.harvard.edu
Tue Jul 1 18:06:59 EDT 2014
Search archives:

Hi Thinh,
   Could you share any plots/images of your unexpected/inaccurate results?
Also, could you motivate why you want to do a dSPM (on a whole brain
basis) given that you have fMRI priors?

As mentioned by Alex, the dSPM/sLORETA normalizations make it such that
everywhere on the brain, the baseline is of unit variance.. This would
indeed negate the fMRI prior weighting because the fMRI prior scales down
some vertices relative to the others (whereas dSPM tends to equalize them
by making them unity)..

In my mind, given that you have an fMRI prior, if you are still interested
in obtaining a z-score type metric, rather than currents, then perhaps one
way to do that would be to mask out the vertices that are not active in
the fMRI before converting to z-score..

HTH,
Hari

On Tue, July 1, 2014 5:54 pm, Thinh Nguyen wrote:
> 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
>> >
>> > _______________________________________________
>> > Mne_analysis mailing list
>> > Mne_analysis at nmr.mgh.harvard.edu
>> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>> >
>> >
>> > The information in this e-mail is intended only for the person to whom
>> it is
>> > addressed. If you believe this e-mail was sent to you in error and the
>> > e-mail
>> > contains patient information, please contact the Partners Compliance
>> > HelpLine at
>> > http://www.partners.org/complianceline . If the e-mail was sent to you
>> in
>> > error
>> > but does not contain patient information, please contact the sender
>> and
>> > properly
>> > dispose of the e-mail.
>> >
>> _______________________________________________
>> Mne_analysis mailing list
>> Mne_analysis at nmr.mgh.harvard.edu
>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>
> _______________________________________________
> Mne_analysis mailing list
> Mne_analysis at nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis


-- 
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





More information about the Mne_analysis mailing list