Dear SPM´ers
I’ve got a question concerning the way to perform a parametric analysis
using weighted contrasts. This question has already been issued a couple
of times, but I still can’t make my mind up …
Here is the point I’d like to solve:
I have a 4 conditions bloc design (let’s say condition A, B, C, D) with
increasing complexity from A to D. In the design matrix each condition is
modelled with an unique regressor; Therefore, testing H0 for A would be
the contrast 1 0 0 0, …, and 0 0 0 1 for D;
I’d like to know if using this design one could extract area that linearly
varied along with complexity; My first guess would be to test the
following contrast;
C = -2*A -1*B +1*C +2*D ie here [-2 -1 1 2]
Based on previous discussions, it sounds that this contrast is likely to
pop out what I’ am looking for but also other mysterious things …
1) does such contrasts have a real sense ?
2) does it show linearly varying betas ?
3) what else does this contrast is likely to show ?
Moreover, could I use the corresponding contrast images (1 con.image per
subject) to perform a second level analysis (RFX)?
Any other inputs for the good and/or best way to perform parametric
analysis (without using the parametric modulation SPM function) are more
than welcome !
Thanks a lot for any help
Best regards
Emmanuelle
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