[pymvpa] rapid event-related design / beta series approach using PyMVPA

[Yaroslav Halchenko]

On Thu, 11 Oct 2012, divadd at web.de wrote:

>    Dear all,
>     
>    I’m a newbie to PyMVPA and I want to analyse a rapid event-related fMRI
>    design (Stimulus presentation: 2s; time between two stimuli: 3,5 s (Jitter
>    of +1s), TR: 2s). I used SPM to build a model where each stimulus
>    presentation forms an own regressor. This gives me one beta image (sample)
>    per stimulus presentation (event). Now I’m wondering if there is a way to
>    use these beta images for classification in PyMVPA.  Can I simply create a
>    dataset (fmri_dataset) of my beta images? 

Sure -- just give filenames with betas in a list.  moreover you can
become even fancier -- do you estimate GLM model with HRF derivatives?
load those as well and hstack two such datasets...  but that is getting
a bit more advanced I guess ;)

> Or is there something special   that I have to consider?

not really -- just make sure to use up to date PyMVPA (version 2.2.0
now)
-- 
Yaroslav O. Halchenko
Postdoctoral Fellow,   Department of Psychological and Brain Sciences
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
Phone: +1 (603) 646-9834                       Fax: +1 (603) 646-1419
WWW:   http://www.linkedin.com/in/yarik