Dear SPM users/experts,
Suppose you have a simple design with two experimental conditions (A &
B) and one control condition (C).
A= interaction between an effector and an object
B= another type of interaction between the effector and the object
C= effector and object but no interaction
The aim is to concentrate and A and B.
After preprocessing, my first approach has been to run A>baseline,
B>baseline and C>baseline at first level for each subject. Then I took
the resulting 'con' images at second level to implement a rfx ANOVA (1
factor, 3 levels). When exploring the results of the ANOVA by running
the following contrasts (e.g. 1 0 0; 0 1 0; 0 0 1) I have noticed highly
significant but also very similar pattern of activation for all three
conditions (A, B, and C). This is also confirmed by the lack of robust
results when subtracting C from A and B. (1 0 -1; 0 1 -1). On the basis
of these results it seems that activation in C is comparable with that
obtained for A and B.
However, when trying to visualize the A (1 0 0) and B (0 1 0) contrasts
exclusively masked with the C contrast (0 0 1) I obtain very robust and
interesting results.
Although masking is different from a canonical contrasts such as A>C or
B>C I was wondering whether this could still be an accepatable procedure
to adopt to present data.
Do I have any other alternative method other than a canonical contrast
to see what is left in A and B after 'subtracting/not considering '
activation evoked by C.
Many thanks in advance to anyone has a spare sec to provide
comments/suggestions.
Best
Andrea
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