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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. Regards, Glad -- Glad MIHAI Funktionelle Bildgebung Uni-Klinikum Greifswald Walther-Rathenau-Straße 46 17489 Greifswald www.baltic-imaging-center.de