[pymvpa] searchlight for data with different runs with different masks

[Yaroslav Halchenko]

On Sat, 19 Dec 2015, Kaustubh Patil wrote:

> Hi,

> I want to use PyMVPA for whole-brain searchlight analysis on some existing
> data. The data has been already preprocessed (skull stripping, motion
> correction etc.). Each subject data contains 10 runs and each run was processed
> separately, so there is a separate full brain boolean mask for each run.

> My question is what is the recommended/correct a way to use this data to
> perform run-wise cross-validation searchlight?

you have a problem here, since you have done per run preprocessing, in
particular motion-correction, your volumes are misaligned across runs.
(used FSL, didn't you? )

ideally, you redo preprocessing while motion correcting to the same
volume across all the runs.  Alternatively, you reslice all the runs
into the same space (could well be the common space your toolkit used
for analysis across runs -- common anatomical or MNI) and then do
analysis there, while again unifying your mask, which must be the same
across all the runs.

> As I understand, each run has to be in the same space (same number of voxels)
> so that training and test can be performed, so the whole brain masks have to be
> somehow aligned. How would you recommend doing this?

it is not a mere 'number of voxels' problem but rather that you have
misaligned across runs volumes.  if just voxel number -- choose
intersection of all masks.

-- 
Yaroslav O. Halchenko
Center for Open Neuroscience     http://centerforopenneuroscience.org
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
Phone: +1 (603) 646-9834                       Fax: +1 (603) 646-1419
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