Dear fMRI DCM experts,
I am new to fMRI DCM and would like to ask for your advices on data analyses.
I have fMRI data of two groups (patient vs. control) of participants who performed a task with two conditions (emotional vs. neutral). There are 5 sessions of 5 blocks in the task. Each block is either totally emotional or totally neutral condition. Emotional condition appears in 1 or 2 blocks per session. I am interested in the neural correlates of the differences between emotion and neutral conditions, and also the between-group differences of the contrast "emotional-neutral". I have two ROIs: L amygdala and vmPFC, which have been defined in the fMRI data analyses.
My questions are:
(1) Following SPM12 manual, I modeled two events: "neutral+emotional" and "emotional" in DCM's GLM. However, should I just model "neutral" and "emotional" seperately (as what I did in common fMRI GLM)?
(2) Following SPM12 manual, I made the F contrast for "Effects of interest" (i.e. neutral+emotional) and two T contrasts (i.e. "neutral+emotional" and "emotional"). However, should I also get the T contrast for "emotional-neutral"?
(3) I extracted time series from each ROI per session per subject. However, should I concatenate all sessions per subject before extracting time series, given that the number of blocks per session are unbalanced between emotional (1-2 blocks/session) and neutral (3-4 blocks/session) conditions?
(4) Following SPM12 manual, I defined the VOI of L amygdala by logically AND two images: [i1] the SPM results of "neutral+emotional" (height thresholded at p < 0.5) and [i2] the sphere covering the predefined ROI of L amygdala. On the other hand, I defined the VOI of vmPFC by logically AND two images: [i1] the SPM results of "emotional" (height thresholded at p < 0.5) and [i2] the sphere covering the predefined ROI of vmPFC. However, can I just extract signals from my predefined ROIs? Or, can I locate the VOI through using the SPM outputs corresponding to the contrast "emotional-neutral", which is more accurate than "neutral+emotional" or "emotional"?
(5) I modified the "dcm_spm12_batch.m" in SPM official sample dataset of attention for my data. However, for the section of "Experimental inputs", I do not understand why there is a "33" in "DCM.U.u = [SPM.Sess(j).U(1).u(33:end,1) ..."
(6) for the section of "MODEL DEFINITION", may I know whether I am wrong to model as below:
DCM.a = [1 1; 1 1]; % the bi-directional intrinsic connections between L amygdala (ROI 1) and vmPFC (ROI 2)
DCM.b = zeros(2,2,2); DCM.b(1,1,2) = 1; DCM.b(2,2,2) = 1; DCM.b(2,1,2) = 1; % task modulations on L amygdala, vmPFC and L amygdala --> vmPFC
DCM.c = [1 0;0 1]; % input to both L amygdala and vmPFC
DCM.d = zeros(2,2,0); % There is no nonlinear modulations
(7) For FFX method, is it correct that the best model is at least larger than the alternative models in 3 unit of log-evidence? On the other hand, I can't find log-evidence outputs in RFX method. How can I judge which model is the best using RFX method?
(8) Am I right to extract the "mean DCM parameters per subject" from BMS.DCM.ffx.bma.mEps or BMS.DCM.rfx.bma.mEps for between-group comparison? If I understand it correctly, the DCM parameter, e.g. 0.123, of task modulation on region A-->B means that if there is a 1 unit neural activity increase in region A, there is a 0.123 unit neural activity increase in region B. Am I right? Is there any other DCM parameters or outputs for between-group comparison?
Thank you very much!
Bests,
Delin Sun
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