Dear Ariadna,
Starting with some general remarks: The concept of a small volume correction is to restrict the analysis to regions with a-priori hypotheses instead of running a whole-brain analysis, the motivation is to end up with a more liberal threshold due to smaller volume. As one would have to decide about thresholding in advance, one would have to incorporate *all* a-priori regions. This is very important. In practice, I have never seen a paper proceeding like that. Rather, it's whole-brain analyses, showing sig. activations in certain a-priori regions, followed by SVC for a-priori regions that failed to reach sig. in the whole-brain analyses. This is bad science. 1) In this context, the decision to conduct a SVC means to lower the threshold only after one has run some analyses (if it had been sig. on whole-brain, there would obviously have been no need for SVC), which is a flaw. 2) The threshold is lowered for *some* regions only, which is also a flaw. One could argue that this is a minor issue, if a region shows up whole-brain, it should also be sig. in a SVC. However, the extent of the activations regarded as sig. might be (much) larger, which could have certain implications, plus, when considering all a-priori regions for SVC, the resulting threshold might be too high so that the initial sig. SVC results for select a-priori regions are no longer sig. It's worth a note that the SVC threshold does not reflect the volume but the RESEL count, which is affected not only by volume but also by surface and smoothness of the residuals. Several small spheres could already result in a relatively large surface.
Concerning 1.: In principle, one can think of two options*. Combine all a-priori regions into a single volume (mask) or run several SVC restricted to single regions, accounting for the number of tests (e.g. in case of five a-priori regions and a chosen initial voxel threshold of .001, go with .001/5). The results will not be identical as the a-priori regions likely differ in volume, surface, smoothness. As an example, think of some low-level vision experiment in which we are only interested in occipital lobe and LGN. The occipital lobe is much larger than the LGN. In case of a SVC on cluster level covering both regions, a cluster would probably have to be quite large to reach sig. in LGN. It might be wiser to run two separate SVCs with an initial voxel threshold .001/2. Whether to go this or that way, well, there are always drawbacks.
* Actually, there's a third one. Combine all a-priori regions into a single volume (mask) and specify this as an explicit mask when setting up your GLM, then run the model and plot and report the results as you would usually do. The whole-brain analysis is now an "a-priori region analysis". These results will not be identical to SVC results derived from a single volume (mask), as some parameters are approximated from the whole-brain volume, that is also from voxels that have never entered the "a-priori region analysis".
Concerning 2: This is correct for SVC on cluster level. Note, however, that SVC is often conducted on voxel level, probably more often than on cluster level - usually resulting in inconsistent threholding = starting with whole-brain analyses with cluster correction, followed by SVC with correction on voxel level. For SVC on voxel level, the procedure is a bit intricate https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1504&L=SPM&D=0&P=450761 .
In general, I would however disadvise from running SVCs. The idea of a SVC is reasonable, but the way it is used turns out to be problematic to such an extent that I would just forget about it. I would rather go with region-of-interest analyses e.g. with Marsbar, plot the average estimates for the different regions and conditions and conduct the analyses based on the extracted parameters. This should be way more informative, after all you're looking at a-priori regions. Please note that this type of ROI analysis does not answer the questions that a SVC could answer, as SVC is about sig. voxels / clusters within a pre-defined volume and not about the average.
Best regards
Helmut
PS: I'm the author of the old message that you had referred to, in the meantime I use a differen mail address for the forum, so don't be surprised.
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