Dear all,
I am intersted to use 3D deconvolve to obtain voxel-wise response functions for event-related data in mice.
Particularly, for my analysis, I aim to investigate a modelled 'nuisance' term that has a unique shape for each individual brain voxel.
Essentially, I would like estimate the response function with and without this term, to evaluate if it would improve estimation of the response function.
I understand that in 3D deconvolve, it is possible to provide nuisance terms (such as motion vectors) in the baseline model.
I however don't know how to provide such terms in a unique way for each respective voxel.
Can anyone please help me?
Thank you in advance,
Michaël
