Hi Gang,

Yes I used the TENT function as the basis function to estimate BOLD response at single subject level and have already averaged those betas for each stimulus condition.

Yes, each voxel was assigned to a specific subregion based on probability information. Each voxel belongs to only one subregion, so that there is no overlap. I guess what I am asking is that I would like the voxels that are most likely to belong to the subregion (like that voxels that have a 90% chance of belonging to the basolateral amygdala) to carry more weight to the average than those voxels that have only a 50% probability of belonging to the basolateral amygdala.

What I would like to apply something similar that is done with resting state data to task data. For example, Roy (2009) does the following:

To minimize effects due to interindividual anatomic variability, each voxel's time series was weighted by the probability of inclusion in a given amygdala subdivision, based on the interindividual variability of the ten subjects used to construct the original anatomic atlas. In other words, those voxels most reliably located in a given region made the greatest contribution to its signal. In each subject, mean time series were then extracted by averaging across all voxels' probability-weighted time series within each subdivision.

Thanks!

Emily