Thank you Rick for your comments/suggestions.
I have a few more questions.

1) You said the voxel level is always the uncorrected p-value, the
corrected p-values apply to the clusters. Does this apply to both FWE (p) and FDR (q)? I am wondering: if I use FDR (q under the slider bar) instead of FWE, do I need to set a limit for cluster size afterwards?
Maybe I am missing something important here?
My understanding is that, if one's already applied an appropriate correction for multiple comparisons (either FWE or FDR) at the voxel level, one should be justified in interpreting that anything shown significant is "significant". There is no need for further corrections. Am I right?

2) I have read the paper: "Cluster-extent based thresholding in fMRI analyses: Pitfalls and recommendations" by Choong-Wan Woo et al. ---------- [www.ncbi.nlm.nih.gov] ------------- in which they state that cluster-extent based thresholding provides low spatial specificity; researchers can only infer that there is signal somewhere within a significant cluster and cannot make inferences about the statistical significance of specific locations within the cluster.
*** With that in mind ... If I want to investigate the evolution of brain activation within some ROI associated with some task over time, is it valid that I measure and look at the change in the number of voxels of some active cluster within that ROI (with cluster-extent correction)?
On the one hand, I think that even I see a bigger cluster (say 500 voxels) at time t2 compared with 400 voxels at a previous time point t1 (same location), I still cannot conclude that there is an effect of (say) 'learning' in that ROI. This is because, as suggested in the paper above, nobody is sure if the additional 100 voxels are actually active. On the other hand, I feel that it is valid if I can observe a consistent trend over multiple time points, e.g. 400 voxels at t1, 500 at t2, 700 at t3, 1000 at t4 etc.
What would you suggest? (I hope the question is clear)

Thank you again for your help.
Duong