Dear Ilenia
Taking a step back from the DCM, please can I clarify your experimental design? You mentioned that had two experimental conditions: light 1 and light 2. Did you also have conditions with no lights (i.e., baseline or null trials) and conditions with both lights, thereby forming a 2x2 design?
Best
Peter
-----Original Message-----
From: SPM (Statistical Parametric Mapping) <[log in to unmask]> On Behalf Of Ilenia Paparella
Sent: 18 March 2022 12:33
To: [log in to unmask]
Subject: [SPM] Bayesian Contrasts DCM
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Dear all,
I am trying to investigate with DCM the effects of two lights on the connections between 2 regions. That's what I did so far:
1. I have estimated a full model (full interconnection between the 2 regions and both lights modulating all the connections) and replicated it across subjects; 2. I checked the variance explained by the model and rejected subjects where the model was explaining less than 10% of the variance; 3. I run a 2nd level analysis (PEB) with no covariates separately for the B and the A matrix and then a PEB automatic search.
If I have only one of the 2 lights changing the baseline connection between my 2 VOIs, then I guess I don't have to do any further analysis. Am I right?
However, if I have both lights modulating the baseline connection I would like to compare the two modulations. In a previous email, Dr. Zeidman kindly told me that the best way to do it would be to have parameters in the B matrix that encode the difference between the 2 lights and then compare the evidence for models with those parameters switched on and off. But I'm not really sure how to do it.
Now my B matrix looks like this:
val(:,:,1) == [0 0; 0 0] input with no modulatory effects
val(:,:,2) == [0 1; 1 0] light 1 modulation on both connections
val(:,:,3) == [0 1; 1 0] light 2 modulation on both connections
How do I compute the difference between the 2 lights in the B matrix and compare the resulting models?
Thank you in advance for your time and help.
Best,
Ilenia
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