Hi,

If your regressors vary across trials, you could convert an epoched dataset to images do a GLM across trials in each subject and then take beta images to the second level. Both within- and between- subject steps are done using the 'Second level' button in SPM. There is an example of an analysis across trials in section 42.5 of the manual. Another way to do the same thing is with the 'Contrast' function where you could use the pseudoinverse of your design matrix as a contrast across trials for an epoched dataset and then treat the resulting dataset as you would an average with multiple conditions.

Best,

Vladimir

On Fri, Sep 2, 2016 at 4:02 PM, C S Sherwell <[log in to unmask]> wrote:
Hello EEG/SPM experts,

I was wondering if the following analysis was possible using SPM12:
I am conducting a spatiotemporal analysis using ERPs converted to smoothed images. I have two covariates and one factor within my design matrix, and I would ideally like to see where in scalp space and when in the epoch a covariate correlates with ERP activity while controlling for the second covariate.
To my understanding, the analogous fMRI analysis would achieve this during first-level analysis, by orthogonalizing one covariate against the other, akin to a step-wise or hierarchical regression analysis.
However, using SPM12 to conduct spatiotemporal analysis, I believe one converts ERPs to smoothed images and proceeds to second-level analysis initially at the participant level, and then at the group level.
Is it possible to conduct a multiple regression analysis using EEG data where a covariate is used to explain the residual variance after controlling for another covariate?
Any help would be greatly appreciated.