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

[Yaroslav Halchenko]

On Sat, 19 Dec 2015, Kaustubh Patil wrote:

> Thanks a lot Yaroslav. I am following a procedure as described below please
> let  me know if it has any clear or potential problems. I am also throwing in
> another questions here but can start another thread if its worth.

> 1) Alignment procedure: Align all the runs to the middle volume of run1
> (example_func from fsl). Use the mask that was generated by fsl form run1.

ok

> 2) MVPA: do the classifiers give balanced accuracy as my datasets are not
> balanced? 

might need rebalancing.  post output of your dataset.summary() here

> Also, is it recommended to run searchlight on betamap (after fitting
> hrf) or zscored raw data? 

whatever fits your bill.  usually betamaps, and possibly z-scored (per
run or across all)

> If betamap after fitting hrf then I using the
> provided function I get only one parameter per target per run, is that how its
> supposed to be?

ok if that is what you want to classify... some times you might
want model each trial separately.  there is no universal answer. 

-- 
Yaroslav O. Halchenko
Center for Open Neuroscience     http://centerforopenneuroscience.org
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
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