Hi Helmut,

I really can't begin to say how much this is helping!!! Really great. My comments below:

>Usually the realignment parameters (rp text file in the preprocessing folder) are added to the design, for that purpose select the rp file as "Multiple regressor". This should result in 6 additional columns for the three translations and the 3 rotations.

I actually didn't do any preprocessing in SPM (I actually assumed that it was done beforehand by the person who gave me the data - except for normalization which I know was not done). After doing the preprocessing (including realignment), where is the place where I can select the rp file as a "Multiple regressor"?

You're right that the data is not normalized, I was planning to do the normalization in FSL, but maybe it looks like it may be easier in SPM as part of those 6 preprocessing steps.

Thanks so much!

Joelle

On Fri, Jun 5, 2015 at 3:50 PM, H. Nebl <[log in to unmask]> wrote:

Dear Joelle,

> the PM should be represented by the 2nd row in your design matrix
This should have read "by the 2nd column". Column = different regressors, row = different time points. Sorry for that.

> Yes, I think I have 3 regressors as you suggest!
Usually the realignment parameters (rp text file in the preprocessing folder) are added to the design, for that purpose select the rp file as "Multiple regressor". This should result in 6 additional columns for the three translations and the 3 rotations.

> If I were interested to test both first (task activation) and second (behaviour PM) together, how can I do this? Something like [1 1 0]?
[1 1 0] tests for the sum of beta estimates for the task regressor and beta estimates for the PM. This is a valid contrast, but it might be meaningless. Maybe you want to see voxels where any effect occurs, be it task or PM? This would be achieved with an F contrast [1 0 0; 0 1 0].

> Do you mean after having done the first-level analysis, to forward the con images into a 1 sample t-test for the second-level (group) analysis?
Yes. This is the two-stage summary statistics approach for mixed effects. Estimate beta values on indiviudal = single-subject = first level, forward these into a group = second-level model. There are special modules for group models, I'd suggest to look at the manual to get an impression of the procedure (again, you'll need a specification module, this time "Facorial design specification" to set up the design, followed by an estimation module).

One note: The attached figure looks like unnormalised data. Of course it's correct, but within SPM the default procedure would be to normalise the realigned data, followed by smoothing (in contrast to e.g. FSL). Single-subject models would be based on the normalised, smoothed data, beta/con images from these single-subject models would be forwarded into group models.

Best

Helmut