Dear Martin et al.
I have a new question about your TDT toolbox.

For my design:
It is a blockdesign, with 2 run.
Each miniblock is made of 8 stimuli of the same condition.
There are 16 conditions.
Within each run, there are 4 “big blocks” with the 16 conditions within each, with the same stimuli, but the order the conditions are presented with is randomly defined within each “big block”.
To summarize: (16+16+16+16) then (16+16+16+16) again. So each condition is presented 4 times across one run, but for the univariate analysis, I have 1 Beta for each condition per run (estimated from the 4 times the condition was presented). 
For the TDT and MVPA: I have artificially divided each run into 4 chunks for the decoding (then it is like (16+16+16+16+16+16+16+16), so I have 4 Beta per condition per run, 8 in total, actually like if I had 8 runs (it seemed better for the decoding design to have 8 chunks than 2). So the classifier trains on 7 chunks, and tests on the 8th.
My questions are:

First, is it possible to give the functional EPI to the toolbox to train and test on, instead of the Beta maps?

Second, since the beta map I get represents the mean activation during a whole condition (so 8 stimuli for a miniblock), I am wondering whether it could be interesting to modify once again my model, and divide each miniblock in a kind of eventdesign, with one Beta for each stimuli, so I would have for the condition A within the each chunk 8 Beta. If I do so, will the toolbox be able to look within the searchlight for each Beta (so kind of a discrete repartition over the time of my activation pattern) or will it juste look within the searchlight for a mean pattern activation across the 8 Beta?

Third point, but which results from the previous ones, would it be possible to get this discrete look of my activation pattern over time for the functional volumes instead of the Beta maps?

Last question but totally different, for decoding methods, there is the classification_kernel, classification and regression. Where could I find some explanations about them? Is it a SVM for the 2 classifications and logistic regression for ‘regression’? I am sorry, I am not quite familiar with fMRI statistics.
Thanks for your help, I am not sure I have been clear enough, don’t hesitate if any precisions are needed.
Fabien.