Hello Marco,
I expect Klaas would be able to give you a fuller reply, but here is
something to start with:
> The model is constituted by 4 anatomical regions, with only one region
> receiving a driving input.
>
> There are two different questions that I would like to address:
> 1. Is the overall functional integration within the system stronger for
> stimulus A vs B (main effect of stimulus (A1+A2)-(B1+B2))?
> 2. Is there a significant interaction between the two factors, such that
> the connection strengths for stimulus A vs B are stronger in the context
> of task 1 vs 2 (interaction (A1-B1)-(A2-B2))?
A good place to start is the attention to motion example dataset on the
SPM website, where a similar problem, with factors 'motion' and
'attention' are crossed factorially. This example is also discussed in
the DCM methods papers by Friston and Willl Penny.
> To address these two questions I have set up a GLM Design matrix with
> two conditions:
> - onset of events of condition A (representing the main effect
> (A1+A2)-(B1+B2)) -> 'STIMULUS'
> - onsent of events of condition 1 (representing the main effect
> (A1+B1)-(A2+B2)) -> 'TASK'
>
> I then defined a DCM model, in which 'STIMULUS' provides the driving
> input, and 'TASK' is allowed to modulate all the defined intrinsic
> connections.
>
> Is the procedure described above so far correct?
>
The model you have described will allow you to test connections modulated
by the main effect of stimulus (your question 1) but not the interaction
(your question 2). One way to test your two questions simultaneously
would be to create 2 regressors, one corresponding to the main effect of
stimulus as you describe above (all A trials) and the other encoding the
interaction (i.e. all A trials in condition 1). You may find it useful to
create a third regressor encoding alll trials ('photic') as proposed in
the example dataset.
> Do I understand it correctly that:
> - The intrinsic connection strengths (matrix DCM.A) represent how the
> main effect of 'STIMULUS' that is induced in the input area is conveyed,
> via the specified connections, to other areas (answer to question 1 above).
> - The modulatory connection strengths (matrix DCM.B) represent the
> degree to which the activity is passed from the input region to other
> areas, depending on the level of 'TASK' (answer to question 2 above).
The intrinsic connection strengths (DCM.A) refer to estimates of
interregional dependency that occur independent of your experimental
variables, i.e. that occur even at baseline. The modulatory connection
strengths (DCM.B) are those peturbations to this connectivity that are
introduced by your experimental variables (i.e. stimulus, task, or their
interaction). So the answers to both of your questions will be found in
the matrix DCM.B.
Hope this is helpful,
Chris
>
> Thank you for your help!
> Best wishes,
> Marco
>
> --
> Marco Tettamanti, Ph.D.
> San Raffaele Scientific Institute
> Facoltà di Psicologia
> Via Olgettina 58
> I-20132 Milano, Italy
> Tel. ++39-02-26434888
> Fax ++39-02-26434892
> Email: [log in to unmask]
>
