[FieldTrip] Single-subject Monte Carlo PLV or WPLI test?

[Matthew Davidson]

Hi everyone, I'm looking to see if there's an equivalent to the
statfun_indepsamplesZcoh function, but for other connectivity
measures, like PLV or WPLI. I need to do several single-subject,
between-trials analyses of differences between two conditions. Since
my data are intracranial EEG, there's no meaningful group test I could
use, which I gather is how many people make inferences on connectivity
measures. So, has anyone implemented this, or something like it? Am I
missing something obvious in how to do this?

If I implement it myself, I guess I should randomly partition the
trials, compute the WPLIs of the two groups, take the difference,
compute the max cluster size, and build a permutation distribution of
the max cluster WPLI difference. Is that generally correct? Should I
use jackknife variance to transform them into Z-scores for
thresholding?

Alternatively, if I wanted to do this parametrically, how should I do
that? (I ask because Monte Carlo methods w/clustering haven't worked
as well as analytic methods on intracranial data where the electrodes
are more independent than in MEG or scalp EEG.) What's the proper
reference distribution of differences in these bounded connectivity
metrics? Do I just compute the jackknife variance, and then do a mass
univariate t-test on the connectivity measures (for a single electrode
pair and freq bin)?

Thanks for any insight or advice you might have,
Matthew Davidson