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Dear Sam This is a good question and helpful for others as it's quite generic. You've got a 2 x 3 factorial design: condition (active vs passive) and valence (positive, negative, neutral). You hypothesise an interaction: a connection from region A to region B should be boosted by positive valence, specifically in the active condition. There are various ways to model this, and when in doubt, you can try different options and compare them using Bayesian Model Comparison. Typically, one factor is used as the driving input and another factor is used as modulation. So in this case, I would drive the DCM using just the active condition (leave the passive unmodelled). And place valence as a modulatory input on the connections of interest. This expresses your hypothesised interaction - valence will only have an effect when stimuli are in the active condition. A little complexity is added by having three levels to your valence factor. One possibility would be to rework this into two modulatory inputs: emotional vs neural and positive vs negative. To do this, you'd need to go back to your GLM and add parametric modulators for these (e.g. 1 for emotional and -1 for neutral). Alternatively, you could keep all three valences separate, and place them on the connections of interest. I think this is a bit less elegant, efficient and interpretable, but easier to implement. Hope that helps Peter -----Original Message----- From: SPM (Statistical Parametric Mapping) <[log in to unmask]> On Behalf Of Sam W. Sent: 10 February 2019 07:16 To: [log in to unmask] Subject: [SPM] DCM questions Hi, I've just started to learn DCM and I was wondering what would be the best way to specify my model. My experimental design consists of a 2 condition x 3 valence. Condition has two levels (active and passive), and valence has three levels (positive, negative and neutral). The example in the SPM manual uses a visual input regressor consisting of every visual stimulus, but this doesn't seem to be the recommendation for factorial designs, so I'm wondering how to use the SPM design I already specified. My hypothesis is that there will be forward connectivity from region A to region B for positive emotional words only in active condition but not in passive condition. So is condition my modulatory input and all words my driving input? Or should I specify only positive words as my driving input? In the SPM design matrix I have the following regressors ActivePos, ActiveNeg, ActiveNeu, PassivePos, PassiveNeg, PassiveNeu With only two regions, and the driving input to region A, my C-matrix should look like 1 1 1 1 1 1; 0 0 0 0 0 0, correct? If active condition has a modulatory effect on connection A to B during positive words, then my B-matrix should be b(:,:,1)=[0,0;0,1] b(:,:,2:6)=[0,0;0,0] is that correct? Thank you! Sam