Dear FSL experts,
I have a question about the use of dual regression (on a FIXed data-set) when one is only interested in few (1-2) components.
Is it sensible to only use the spatial maps of these components as input or does it actually make sense to include a couple more meaningful components?
The rationale behind the question is the following:
If the multiple regression behind dual regression works with partial regression coefficients (and components are not completely spatially independent), I would assume that by including more components, the time-course that is attributed to my components of interest is somewhat cleaner, as time-course variance pertaining to one of the other components will be attributed to those other components and not (erroneously) to my components of interest.
Not sure if this makes sense - statistically and with respect to the workings of dual regression - so I am grateful for any feedback!
Cheers,
Helen