Dear Peter,
thank you very much for your answer.
In fact, I found a mistake. Now the BMA result seems to be congruent with the subject- and model-specific EP.B. I just mixed up the model order. Sorry for this.
Indeed, in regard to question 1, the winning model was the one with an empty B matrix (applying DCM to an event-related design with only one condition = GRIP).
Some months ago, we had a conversation about this issue. As suggested by you, I applied a fully connected A matrix and various B matrices including one empty (zeros) B matrix to account the for the redundancy of B and C (input, 8 different ways = families). https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1502&L=SPM&P=R62792&1=SPM&9=A&I=-3&J=on&X=7AD9ED59112B08C20B&Y=rbrts%40gmx.de&d=No+Match%3BMatch%3BMatches&z=4
In 4 subjects, the only winning B matrix was obviously not able to catch information flow in addition to A matrix and C input. Hence, the empty B matrix model was selected to be the winning model (the only model in occams window of the BMA across all families).
May I ask you: How would you interpret this result? There is no specific grip-related effect which is not covered by A+C, right?
Should I include these subjects (with winning empty B = all zeros) in the analysis? The analysis will be conducted on the coupling parameters (derived from BMA) of the B matrix. Or would I have to exclude these subjects?
Or would there be another way to follow?
If you still prefer the BMS.mat (>20MB), I would need to redo the analysis on a few subjects only.
Thank you very much for your help,
Best,
Robert
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Dear Robert,
Please could you send me your BMS.mat relating to question 1, so that I can see what you mean? Please zip the .mat file, or it'll be removed by my virus checker.
Thanks,
P
-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On Behalf Of Robert Schulz
Sent: 03 October 2015 09:42
To: [log in to unmask]
Subject: [SPM] Odd BMA results in DCM12 SPM v6470
Dear all,
I have realized a problem with BMA in DCM12 (SPM12, v6470).
I conducted a DCM study, my model space comprised 36 models (varying B matrices) x 8 families (varying C matrices) = 288 models for each subject.
Applying RFX BMS I found that no family showed superiority compared to the other. Hence, I used RFX BMA over "all families" to calculate subject specific posterior means "mEPs" over all models in the OCCAMS window for each subject.
I realized the following problems:
1. Some of my subjects had only one model in the occams window. However, in the BMA_mEPs I have only an empty B matrix (all zeros) for that subject. In contrast, the model specific Ep.B (the model in the occams window) showed reasonable connectivity values. This doesn't make sense to me.
2. Some of the subjects had two models in the occams window, for instance model 1 with 4 and model 2 with 8 non-zero connectivity values in the B matrix. After BMA I realized that the posterior means mEPs.B only showed 2 non-zero connectivity values. Also in this case I wonder whether there would be an error during BMA. As I understand BMA, the Ep.B of the different models in the occams window should be averaged, weighthed by the model probabilities. In my example I wonder whether this should give me a BMA mEPs of 8 non-zero connectivity values (the higher number of connections in model 2).
Any help on this issue would be highly appreciated.
Thank you very much,
Best, Robert
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