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```Dear MJ

I wanted to extract subjectwise connectivity values from a full model of 5 regions (R1, R2, R3, R4 and R5) i.e., subjectwise connectivity values of 25 connections (5x5 matrix) in total (e.g., from R1 to R2, R2 to R1, R1 to R3, R3 to R1, R1 to R4, R4 to R1, R1 to R5, R5 to R1, R2 to R3, R3 to R2 and so on...).

I have already generated full DCM model for each subject. From the instructions on this page: https://en.wikibooks.org/wiki/SPM/Parametric_Empirical_Bayes_(PEB), it seems that the next step is to estimate all the models using following command:

GCM = {'DCM_subject1_model1.mat','DCM_subject1_model2.mat';

'DCM_subject2_model1.mat','DCM_subject2_model2.mat'};

% Fully estimate model 1

GCM(:,1) = spm_dcm_fit(GCM(:,1));
Could you please confirm if thats correct?

Yes looks good.

If so, I am not sure what's the next step to get subjectwise connectivity strength values for 25 connections (with and without adjusted for age and sex). Would it be following steps:

% Specify PEB model settings (see batch editor for help on each setting)

M = struct();

M.alpha = 1;

M.beta  = 16;

M.hE    = 0;

M.hC    = 1/16;

M.Q     = 'all';

% Specify design matrix for N subjects. It should start with a constant column

M.X = ones(N,1);

% Choose field

field = {'A'};

% Estimate model

PEB     = spm_dcm_peb(GCM,M,field);

save('PEB_example.mat','PEB');
If so, again I am not sure where will I find the subjectwise connectivity values (25x25 matrix)?

I think you mean the 5x5 matrix? You can view these graphically using:

spm_dcm_peb_review(PEB);

The drop down menu at the bottom left contains will create a popup figure with the matrix. Alternatively, using code, PEB.Ep contains the connection strengths (their expected values) and PEB.Cp contains their covariance. PEB.Pnames indicates the name of each connection.

Best
Peter
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