Hi Drew,
> If we were to concatenate all three sessions, would the scale of each time series be in the same metric? If this is not the case, are there any sets I can take to correct this issue?
It's best not to concatenate, but if you need to, you'll need to add an extra regressor for all but one session in your GLM. I.e. given three sessions, you'll have a column marking every scan from session 1 and a column for every scan from session 2. These will model the mean for each session. (You shouldn't have a regressor for the last session, or your model will be over-specified).
> In the event that we were not to concatenate sessions but to average parameters across models after model selection for parameter comparison between groups, are there any guidelines in the event that one or two of three sessions does not show significant activation in our VOIs?I'm aware that it is standard to remove single subjects from analysis if they do not obtain significant activation in VOIs, but what about single sessions?
In general I would include all sessions and subjects, not just those showing the effects at the individual level.
> Lastly on parameter interpretation. For the connection A-->B, increases in activity of B correspond to 10% of the activity in A per unit time when the parameter is 0.10. Can these values exceed 1.00 and if so how could this be interpreted?
Someone else may know better than me - but I believe they can go over 1, which would mean a value of 1.1 would mean region B increases by 1.1 times the activity in unit A in the context of your modulation.
Best,
Peter.
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