Hi folks,
I'm wondering what would be the appropriate way to do clustering
permutation stats with a bunch of time courses extracted from multiple
labels. Currently I'm using our MNE-Pythion "permutation_cluster_test" with
an f-test (repeated measures ANOVA).
However this can lead to pseudo-spatial clusters just because one label is
put next to another label in the data ndarray. My hunch would be to pass a
custom connectivity matrix that only connects temporal features but not the
spatial ones. But how exactly should it look like?
I've opened this issue for discussion + proposals for additional examples +
documentation:
https://github.com/mne-tools/mne-python/issues/1176
Cheers,
Denis
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