Dear DCM experts,
While playing around with DCM/PEB, I discovered a few things that I'm
not quite sure how to interpret. For context: I ran `spm_dcm_fit` to fit
DCMs for different subjects, then ran `spm_dcm_peb` with different
covariates and finally used `BMA=spm_dcm_peb_bmc` to 'prune' parameters.
I found that it is possible to get results as follows:
Example 1) [Using fields={'B'} for the PEB]
BMA.Pp of B(1,2,3) for the commonalities is (very very close to) 0,
while BMA.Pp of B(1,2,3) of a covariate is >0.95. Would this mean that
across subjects, there was no evidence for modulation from input 3 of
that connection, but the model that best explains individual differences
does include such a modulation?
Example 2) [Using fields={'A', 'B'}]
BMA.Pp of a connection A(1,2) is pretty much 0 for both commonalities
and all covariates, but BMA.Pp of the modulation of that connection
(e.g. B(1,2,3)) is non-zero for one of the covariates.
What would be the correct interpretation for each of the two example
results above?
Some additional information:
- Using the latest SPM/DCM version (7487)
- variance explained is >10% for all subjects
- M.X is a column of ones and columns of zero-mean-centered covariates
- M.Q = 'all'
- M.maxit = 256; convergence before maximum of iterations are reached
Please let me know if any more information is needed to interpret the
results above.
Thank you and best wishes
Sam
|