Dear SPM fans,
I have the following problem. In my design I use FIR covariates to find
sequential activation in different areas of the brain from a motor and
sensory task. I was inspired by the paper of Windischberger et al
(Journal of neuroscience methods, 2008). Now, depending on how many
covariates I include in the design matrix, I get a different type of
activation. As far as I understand, this has got something to do with
the degrees of freedom, which depends on the number of covariates.
I have included three images as a comparison. The design matrix of each
has the HRF model, a number of certain FIR covariates and the motion
parameters at the end (+ constant).
All three images are from the same subject; the TR is 514 ms.
For 14_covariates.png I have used a total of 14 FIR covariates (1 to
15). Covariate 0 (not included in this design matrix) corresponds to the
cue onset. The figure illustrates the activation for covariate #6. As
you can see there is a very nice expected SMA activation.
For 26_covariates.png I have used a total of... well 26 FIR covariates
(0 to 25, 0 corresponds to cue onset). The contrast shows activation for
covariate #6. The expected SMA activation is missing.
For 1_covariate.png only one FIR covariate was used corresponding to
covariate #6. I get no suprathreshold activation whatsoever.
Why is there this difference? Furthermore, what would the optimal design
matrix look like?
I'm looking forward to your answers.