[Mne_analysis] Advice on morphing

dgw dgwakeman at gmail.com
Thu Oct 8 10:00:50 EDT 2015
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Hi Natalie,

IMO
a modified version of option 1 is the best option. Morph the labels to
the individual's space.

Then, instead of morphing the later inverse solutions back to
fsaverage, simply extract the data only from the group defined labels
and run stats on the label data only. This strategy reduces the amount
of morphing and fits your hypothesis that the fMRI labels contain the
activity of interest (which the strong fMRI prior will make happen
anyway). The subsequent morphing would not accomplish anything (except
possibly introduce erroneous smoothing), because the labels are
derived from the average space anyway, so each label is equivalent in
the different participants.

hth
d

On Thu, Oct 8, 2015 at 9:09 AM, Natalie Klein <neklein at andrew.cmu.edu> wrote:
> Hello,
>
> I want to use a group-level fMRI map (in fsaverage space) as an fMRI prior
> for MNE source localization. I also want to define labels from the fMRI map
> that can be used for all subjects.
>
> Previously, I created source spaces for all subjects in each one's
> individual anatomical space. I could not find any tools that allow me to
> morph these source spaces to fsaverage before doing forward/inverse solution
> - it seems most morphing procedures are designed to be applied after the
> inverse solution. So it seems my options are:
>
> 1. Use the individual source spaces for the forward solution. Morph the fMRI
> prior to each subject's individual space to do the inverse solutions. Define
> labels on group fMRI map and then morph labels to each individual space for
> analysis (or tediously draw labels on each morphed fMRI prior map).
>
> or
>
> 2. Redo the source spaces: morph all subjects to fsaverage space with
> mne_setup_source_space and perform forward/inverse solution and all
> remaining analysis in fsaverage space.
>
> Any advice or opinions on the best way to proceed? Option 2 seems best as
> there is less morphing overall, but I would appreciate input/advice.
>
> Thank you,
>
> Natalie
>
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