Hello all, thanks for all the very useful suggestions, it's nice to have so many people thinking with me! I have tried a few suggestions with for each returning the same results (approximately): - I have tried a linearNuSVMC, this gives approximately the same results. - I tried a Odd/even splitter instead of a NFold splitter --> approx the same results - Detrending the data --> approximately the same results. - I have randomized the labels of the two categories. This resulted in the same distribution of accuracies as with the correct labeling (peak of histogram at 0.6 accuracy)..... Does this mean that there is contamination across chunks???
The design of the fMRI task is as follows: The task exists of 38 trials = 38 chunks One trial consists of the following sequence of events: - 4 sec category 1 - 2 sec fixationcross - 4 sec category 2 - 2 sec fixationcross - 4 sec other event (of no importance) - random inter trial interval between 2 and 12 sec Thus total trial duration is between 18 and 28 seconds. So, in each trial/chunk both category events are presented once. The order of category 1/2 in the trial is randomized. So in some trials first 1, then 2 or viceversa. Onsets of events category 1 and 2 are thus 6 seconds apart, but order is randomized so I would not expect problems. Between chunks is also enough time I would expect... Indeed, I have used blockaveraging. For this the functional scans between (approx) 3.6 and 6 seconds after onset of the event are averaged. TR is 0.61 secs. Does anyone have any additional suggestions? Thanks in advance! Best regards, Nynke _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa
