Dear DCM experts,
I have analyzed 35 subjects perceptual decision making data using DCM. I used BMS to find the optimal model (model number 5) out of 10 defined models and also used BMA to interpret about the parameters by averaging over all the models over all the subjects. Each of the model contains 4 areas e.g. a,b,c & d.
I have 2 very simple questions:
1). My winning model, model number 5 e.g. contains facial affect modulating from region a to b, a to c & a to d- using BMS.
whereas BMA results show there is no significant modulation by that facial affect from region a to b, a to c & a to d.
And similarly for significant intrinsic connections as well.
So is it always true that connections/modulations on the winning model should match with the significant endogenous/modulatory parameters obtained from BMA.
If not, then why it should not match ?
(I understand from Dr. Friston's paper about- 'Ten simple rules for DCM' that we use BMS to infer about model structure & BMA to infer the parameters and BMA abandons the dependence of parameter inference on particular model chosen.)
2). If these should be matching then can I use BMA to average over only optimal models over all subjects or is there any other way/approach available to match both?
Thanks a lot !!
Regards,
Sahil Bajaj
