Dear FSL experts,
In some previous posts, I read that it is possible to run a gPPI in FSL by "forming a series of interactions, 1 for each condition by multiplying the condition by the seed region. Then form the model using N interaction terms, N task regressors, the seed region regressor, and any covariates you had in the original task model" (according to Donald McLaren).
However, I am wondering whether it is also possible to include parametric modulators/regressors (as far as I know this is possible for gPPI in SPM)?
Let's say I have the following regressors (R):
R1: simuli condition A
R2: parametric modulation of R1 (e.g., intensity values of stimulus)
R3: stimuli condition B
R4: parametric modulation of R3 (e.g., intensity values of stimulus)
R5: stimuli condition C (not parametrically modulated)
Here, I would be particularly interested in the functional connectivity related to the parametric modulators, for instance, whether the intensity-related changes in functional connectivity differ between conditions A and B. For instance, increasing stimulus intensity might be related to a more strongly increasing functional connectivity between two regions in condition A than in condition B.
Is it possible to construct a gPPI model in FSL that allows to test for such an effect and how?
Thanks!
Stefan
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