Dear MVPA experts,
In my study, I used the fMRI signals from a given ROI to predict the stimulus
type for two different classification tasks: (1) type A vs. type B, and (2)
type C vs. type D (the two classification tasks were performed on the same ROI
but during different trials: the fMRI data used for task 'A vs. B' were taken
from trials A and trials B, and the data used for task 'C vs. D' were taken
from trials C and trials D). It was expected that this ROI should provide a
higher classification accuracy in the task of 'A vs. B' than in the task of 'C
vs. D'. The results indeed confirmed this. I just wonder whether the higher
classification accuracy in the task of 'A vs. B' (presumably the higher
capability of the classifier in task 'A vs. B') relative to the task 'C vs. D'
could be reflected in the sensitivity maps (i.e., SVM weights) in some way? For
example, would the SVM of task 'A vs. B' have higher SVM weights or a larger
margin compared to the SVM of task 'C vs. D'? In other words, can I directly
compare the sensitivity maps obtained from the two different classification
tasks?
I'm not sure if I asked my question clearly. Please let me know if there is
anything unclear.
Many thanks!
Meng
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