Hi Folks, I’am quite new to pymvpa and am currently trying to implement searchlight analysis on group level. I ran an fMRI study where subjects had to discriminate the orientation (vertical versus non-Vertical) of a masked stimulus and rate their subjective awareness of the orientation (1-4 scale). So the targets/classes to be decoded are the orientations. However, I want to know whether orientation information persists on unaware trials. So far I‘ve been able to run the analysis with an NFoldPartitioner on a dataset that contains unaware trials only, but i actually want to train the classifier on all trials (awareness 1-4) in run 1-9 and test it on the tenth run only on unaware trials (awareness 1) in a leave-one-out fashion. So (I think) the crucial part that troubles me right now is to adjust the partitioner. I‘ve been looking at the sifter and the factorial partitioner documentation, but am still not sure about the implementation in such a case.
I appreciate any comment or suggestion. Best, Lasse Güldener M.Sc. Department of experimental Psychology Otto-von-Guericke-University Magdeburg _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list Pkg-ExpPsy-PyMVPA@alioth-lists.debian.net https://alioth-lists.debian.net/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
