Hi all,

I am working on an analysis for a study design on 'effort'. We are
hypothesizing that neural activity related to effort will increase over
time for our 'effort' events.

I am attempting to model this using parametric modulators, which I believe
is the correct approach. But I have no direct experience using parametric
modulators and thus would prefer to check my work with the list before
showing results to co-authors.

We have 6 sessions per person. I am not interested in session x effort
interactions at this time (due to the nature of the experiment), but wish
to identify voxels where the neural activity to our effort events increases
over time. So, I added a 1-st order time modulation. We actually have 2
event types, and I added a modulator for each, and ran the GLM using an HRF
only model for now.

So my design matrix has 4 columns per run [type1, type1*time, type2,

if I want to find voxels where activity increases over time for event
type2, can I just run a contrast of 0 0 0 1? I think this is explicitly
effect of time after removing task effects, and thus doesn't have the sort
of issues (task-default switch, visual activation, etc.) with a main
effects contrast of a task event (like 1 0 0 0).

Any advice and/or confirmation that I am on the right track would be