Dear Rik and Christoph,
In response to the question whether you could use 2 event-related regressions as direct(G) and modulatory(H) inputs respectively: I think this is perfectly fine. It would allow you to model H-dependent effective connectivity from an area driven by G on a second area.
The effects of the modulatory (B) inputs are simply additive to the fixed/endogenous connectivity, and there are no constraints for any durations for B.
For example, suppose you have two regions, x1 and x2, and condition G is the direct input to x1, while H is the modulatory on x1 --> x2. This would test for an H-dependent influence of x1-->x2, where x1 is only active when G is present. (assuming positive input parameter estimates).
best,
Hanneke
4. If the GLM in an SPM.mat file has two event-related
regressors for conditions G and H (and a jittered SOA so
that responses vs the inter-event baseline are estimated
efficiently):
4.1 does it make sense to use
one of these as a driving input (eg, to both of two regions,
eg, DCM.c = [1 0; 1 0]) and the other as a modulatory input
(eg, DCM.b(:,:,1) = zeros(2,2); DCM.b(:,:,2) = [0 1; 1 0])?
An event-type modulatory input would only modulate the intrinsic
connectivity for a very brief instant, while neuronal activity lasts
much longer. Mathematically it is ok but I don't think it makes much
sense.
I would be happy to hear Klaas (or other experts) opinion about
this.
--
Hanneke den Ouden, PhD
Donders Centre for Cognitive Neuroimaging
PO Box 9101, 6500 HB Nijmegen
The Netherlands
Tel: +31 (0)24 36 11757
Fax: +31 (0)24 36 10989
Visiting address:
Trigon, room 0.64
Kapittelweg 29, Nijmegen
