[Mne_analysis] Difference between mne_make_movie & python apply_inverse?

[Denis-Alexander Engemann]

Alex, Eric,

thanks, your reply match my intuitions, I'v never shared though.
So the morph matrix saves you some time given you intend to morph many conditions from one subject to fsaverage, yes makes sense. Although I have to say, using n_jobs -1 morph data for all of my conditions is just a matter of 3 minutes...

Cheers,
Denis


On Thu, Jan 24, 2013 at 10:38 PM, Eric Larson <larson.eric.d at gmail.com<mailto:larson.eric.d at gmail.com>> wrote:

The morph precomputed should give equivalent results to morph_data, but it allows the user to only compute the morph matrix once, which can be more efficient depending on the use case.

I generally morph to fsaverage for three reasons. One, I've stared at that brain longest, so I recognize features on it more quickly. Two, when doing across subjects tests, morphing all subjects to a different brain (fsaverage) avoids any potential bias (such as not smoothing as much in a transform) that could otherwise favor the one subject everyone else's data is morphed to. Three, fsaverage is a grade 5 (20484 vertices total) source space and thus higher-resolution than my other subjects, which typically have around 7000 total dipoles. Morphing to a higher resolution should help minimize loss of spatial information in the transform.

Eric


On Thu, Jan 24, 2013 at 1:30 PM, Alexandre Gramfort <gramfort at nmr.mgh.harvard.edu<mailto:gramfort at nmr.mgh.harvard.edu>> wrote:
hi denis,

> while we are at it, is there actually one to be preferred way of morphing,
> i.e. morph_precomputed vs morph_data?

morph_precomputed is faster but requires more memory. It gives the same output
as morph_data.

> Also is there any theoretical pro /
> con for choosing fsaverage vs inter-subject-morphing?

do you mean morphing to the average brain of your study or one random subject?
I am used to morph to fsaverage so I cannot really comment based on prior
experience.

Alex
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