[Mne_analysis] tf_mixed_norm group solution?

[Alexandre Gramfort]

hi Per,

> Is there a way to force tf_mixed_norm in the python package to generate a
> single set of localizations which can be applied to 1) multiple subjects
> and, 2) multiple experimental conditions within the same subject?

sadly no.

It has never been written although it is "just" an engineering
problem and not a "science" problem at least for the multi condition case :)

> With regard to multiple subjects, since each subject would require an
> individual forward solution, even if they were being morphed to a common
> space in the end, this does not currently seem possible?

indeed you could use a morphed source space but you would still
have to pass each forward solutions unless you find a way to avoid it
by some clever preprocessing. I don't know how.

> A single, average forward solution could be created that spanned conditions
> within a single subject, which could then be applied to the concatenated
> evoked averages for the individual conditions. The time courses of the
> single set of localizations could then be re-segmented into the separate
> conditions. This would require some scheme to minimize the artifact
> generated by the discontinuities, but it could be done?

yes that sounds really reasonable. Let us know if you need
help to look into this.

> Thanks for everyone's help,

no pb

Best,
A