Computing the Y Value for within-task comparisons using Region Based Analysis.

I have a dataset where participants performed: two tasks under two conditions
Let’s say the design looks like this:

TaskA - condition1(TAc1)
TaskA - condition2(TAc2)
TaskB- condition1 (TAc1)
TaskB- condition2 (TBc2)

Based on the literature a am interested in looking at the differences in activation between tasks and conditions in 30 regions of interest. I also would like to use a bayesian approach as the previous has indicated some directionality in the kinds of activations (increase / decrease) should be expected.

If I am interested in the differences between conditions within each task then should The Y-value to used in RBA be (TAc1- TAc2) and (TBc1 - TBc2) ?

Similarly, if I am interested in between task-comparisons for each condition should the Y-value used in the RBA be (TAc1 - TBc1) and (TAc2 - TBc2) ?

Lastly, should each contrast be modeled separately at the group level, and if so - is there a need for a correction?

Thank you for your assistance,
Gerome

Gerome,

If I am interested in the differences between conditions within each task then should The Y-value to used in RBA be (TAc1- TAc2) and (TBc1 - TBc2) ?
Similarly, if I am interested in between task-comparisons for each condition should the Y-value used in the RBA be (TAc1 - TBc1) and (TAc2 - TBc2) ?

The answer to both questions is YES: you perform four separate analyses, one for each contrast.

should each contrast be modeled separately at the group level, and if so - is there a need for a correction?

Even under the conventional AVOVA framework, there is no easy solution for controlling of FWE in this context. As long as all those four comparisons are planned analyses, I would not worry about it.