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Hi Mite,
Thank you for taking the extra effort to help with the analysis. I have sent you an email.
Shrikanth
Hi Mite,
I was wondering if you had time to think about my query, on how to proceed from the group DCM to graphs. If the estimated effective connectivity matrix from DCM can be interpreted as a weighted adjacency matrix of a directed graph between the brain regions. For the Braph pipeline implementation, the group DCM could be treated as a single subject, would this be feasible?
Looking forward to your feedback.
Thank you,
ShrikanthHi Mite,
Thats great! Thank you.
We want to analyse the graphs and its metrics using the full A-B-C connectivity matrices.
I have a basic question about using the matrices for each subject, would it be possible to just use the (single) group level A-B-C matrices for the graph analysis?
The reason I ask is because in our DCM analysis we did not have a clear hypothesis about the network architecture for the five task relevant brain regions. We therefore used a “data-driven” approach, with Parametric Empirical Bayesian method (PEB) to identify the connectivity structure. As far as I understand, PEB seeks the optimal model by testing various combinations of A-B-C-parameters through a pruning process, the winning model is therefore estimated at the group level instead of the individual subjects.
Let me know if you need any clarifications or more information.
Shrikanth
Hi Mite,
Thank you for the information and help.
Since I am short on time to perform the graph analysis (for a revision), I can implement the pipleine for the analysis, with your help.
I downloaded the latest version of Braph 2 from the repository. From its folders I can see that the code for graph metrics and analysis is already there.
To begin, how can I proceed with moving the DCM data (from SPM) into Braph 2?
Shrikanth
