I have ERP  data of two conditions (Suppose A and B). Based on the data i created two models F and FB.

I fitted the data on individual subjects.

I found on the group level :(1) F model was preferred over FB model in  condition A

                                       (2) FB model over F for condition B.

However, then i found that few participants who show a correlation to behavioural data (in my case faster reaction time)in condition A preferred FB model though F model was winning over there at group level.

This motivated me to take the connection parameters (posterior means) of the non winning models too. Then i compared for significant connections between the F models  connection posterior means for 2 conditions and FB models posterior means for the two conditions, to see what variations in connections can cause such outcomes

In general i always found in DCM papers that only winning models are preferred.

In this regards i would like take the view of DCM experts, if this could be done.

Regards

Rajan

PhD student