Dear Peter,
I would like to to know the accuracy of spectral DCM model to predict the connectivity and hemodynamic parameters for a subject from DCM parameters of group of subjects.
Can I do something similar to the following lines?
If this code is correct, how can I setup the hemodynamic parameter in field cell array?
Mean_effect=ones(20,1); % one group of 20 subjects
CP_4_5 = [GCM(1,1).Ep.A(4,5); GCM(2,1).Ep.A(4,5); ........; GCM(20,1).Ep.A(4,5)]; % connectivity parameters from connection 5 to 4
field = {'A(4,5)'};
M.X = [Mean_effect,CP_4_5];
[qE,qC,Q]=spm_dcm_loo(GCM,M,field);
Best regards,
Arkan
________________________________________
From: Zeidman, Peter <
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Sent: 20 June 2018 11:13
To: Arkan Al-Zubaidi;
[log in to unmask]Subject: RE: [SPM] Accuracy of DCM model
Dear Arkan
The Leave-One-Out (LOO) function is intended to check whether your effect sizes (DCM parameters) are large enough to predict subject-level covariates (e.g. group membership or behavioural scores). However, you say you want to predict unseen subjects' effective connectivity parameters, in order to validate DCM. I don't understand that. Please could you clarify the validation you are trying to perform?
All the best
Peter
-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:
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Sent: 19 June 2018 16:55
To:
[log in to unmask]Subject: [SPM] Accuracy of DCM model
Dear SPM list,
I know that the spm_dcm_loo function is for distinguishing (classify) between two groups if the subject is unseen.
Here, I would like to validate the spectral DCM model to predict the unseen subject parameters (effective connectivity and hemodynamic) for one group.
How can I use the spm_dcm_loo function in this case?
I would like to plot the expected parameter and the real parameter (not the classification).
Regards,
Arkan