[pymvpa] classification based on individual parameter estimates from FSL

[Michael Hanke]

Hi,

On Tue, Jul 01, 2014 at 12:25:40AM +0100, David Soto wrote:
> Hi Michael, indeed ..well done for germany today! :).
> Thanks for the reply and the suggestion on KNN
> I should have been  more clear that for each subject I have the
> following *block
> *sequences
> ababbaabbaabbaba in TASK 1
> ababbaabbaabbaba in TASK 2
> 
> this explains that I have  8 a-betas and 8 b-betas for each task
> AND for each subject..so if i concatenate & normalize all the beta data
> across subjects I will have 8 x 19 (subjects)= 152 beta images for class a
> and the same for class b

Ah, I guess you model each task with two regressors (hrf + derivative?).
You can also use a basis function set and get even more betas...
> 
> then could I use SVM searchlight trained to discriminate a from b in  task1
> betas and tested in the task2 betas?

yes, no problem.

Cheers,

Michael

PS: Off to enjoy the quarter finals ... ;-)


-- 
Michael Hanke
http://mih.voxindeserto.de