Dear experts,
This summer lots of messages were exchanged on this list regarding how to best threshold SPM t-maps, and the use of cluster-extent statistics. These, as I understand, are computed correctly under the models implemented in SPM only if the initial cluster defining threshold is high enough.
As I often work with dementia PET images, the signal is generally characterized by an extremely large spatial extent, therefore cluster extent seems a very important parameter to study, therefore I'm reading lots regarding this topic.
I've stumbled upon this paper: Smith, S. M., & Nichols, T. E. (2009). Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage, 44(1), 83-98.
It seems extremely sensible. Has anyone implemented it? Are there any known problems with their solution?
Thank you very much,
Luca
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