> When I searched the literature, I found some applications using SPM
(e.g.
> "Functional connectivity in the resting brain: A network analysis of
the
> default mode hypothesis, Greicius et al, PNAS 100:253-258), thresholds
> their
> results at HEIGHT threshold p<0.01 and EXTENT threshold p<0.05. What's
the
> connection or difference between this HEIGHT and EXTENT p value and
the
> corrected p value?
The cluster-extent correction typically works in two steps: first
applying a height threshold (also known as the primary threshold, or
cluster-defining threshold), then second calculating corrected p-values
for the cluster extents formed at that height threshold. In the example
you presented, I imagine the primary threshold was p<0.01 (uncorrected,
based on T-map intensity) and the clusters were selected for having
corrected p-values p<0.05. Needless to say, these results probably
weren't generated by the combined extent-peak test of Poline et al.
> Given an SPM map (e.g. t-score map), how can I get the
> HEIGHT and EXTENT p value (corresponding to a certain t-score and
cluster
> size, I believe) using SPM? It would be great if you can point me to
some
> instructions or literatures on how to do this.
SPM by default produces and displays corrected and uncorrected p-values
for clusters and local maxima when you assess the results from an
analysis.
-Satoru
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