Thanks for this quick reply, Peter!

Best, Christina

 

 

Dear Christina,

Many thanks for reporting this and for your detailed analysis. Your proposed solution is nearly right (it wouldn’t allow for multiple parametric regressors). I have now fixed this for future SPM releases and I attach the fixed version of spm_dcm_U.m. Please let us know if you have any more difficulty with it.

 

Best,

Peter

 

 

Dear SPM Mailing list users,

we set up a design matrix with two task-regressors, the second one including a parametric modulator, modelling linear and quadratic changes (2^nd order).

SPM.U thus has two entries, where

SPM.U(1) = task1, and SPM.U(2) = task1 pmod1 pmod2

We encounter problems setting up a DCM in which we include all 4 inputs - not during the original model specification with the GUI but when adjusting the DCM for a new participant in DCM input specification

matlabbatch{1}.spm.dcm.fmri.inputs.val  = {1,[1 1 1]};

The model estimation gets errored out because of lines 66-69 in spm_dcm_U.m (error(['More parametric modulations specified than exist ')

For i=2 (second regressor)  

mo = find(inputs{i}) is 1 2 3 and its length is therefore 3.

Therefore, length(mo)-1 (=2) is in fact greater  than length Sess.U(i).P (=1) and the error is true.

We can, however, run the model if we replace length(Sess.U(i).P) with Sess.U(i).P.h (which returns 2 in the case of 2 pmods) and the respective U structure seems indeed appropriate.

Has anyone else encountered this and does this signal that it is actually discouraged to utilize DCM for a higher than 1^st ord pmod modellation design?

We would appreciate your input on this.

Best regards and thank you,

Christina

Christina Regenbogen | Postdoctoral researcher
Dept. of Clinical Neuroscience | Karolinska Institutet
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