(1) voxel-wise tests. These include FWE and FDR. The downside to these are that they correct for individual voxels and it is unlikely the a single voxel would be active on its own. Adding an extent to FWE/FDR corrections makes it an even more conservative test.
(2) Topological FDR - FDR correction of all the peaks in the data. Again, if you have clusters of single voxel it can be hard to interpret. This does not depend on cluster extent, just on the peaks in the data.
(3) Cluster extent. This includes: FWE, Topological FDR, and monte carlo simulations (e.g. 3dClustSim). These methods identify clusters that reach significance. The results allow you to make inferences of the clusters, but not the voxels in the cluster (unless you revert back to #1 or #2.
Hope this helps.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Website:
http://www.martinos.org/~mclarenOffice: (773) 406-2464
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On Sat, May 5, 2012 at 10:42 PM, 伪影
<[log in to unmask]> wrote:
Dear spmers
I have a question about what is correction based on cluster threshold. Someone said that" When using the standard linear modeling approach as described by Friston and Ashburner, it is currently customary to report locations of peak activity only if they fall within clusters that survive a p<0.05 corrected cluster threshold level". I 'm not clear about it. Can you tell me what the definition the "correction based on cluster threshold" is and how to realize it? I wonder whether the FDR correction is a method of "correction based on cluster threshold". Any suggestion would be appreciated.
Best Regards,
Li