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

Eric Maris e.maris at donders.ru.nl
Fri Feb 18 10:36:36 CET 2011

Hi Matthew,

Permutation inference is valid for comparing two experimental conditions
using ANY statistic. If your channels are more or less independent (no
common pick-up via volume conduction), then don't use the cluster-based
statistics (at least not for the spatial dimension; clustering along the
spectral dimension may still be wise). 


Eric Maris

> -----Original Message-----
> From: fieldtrip-bounces at donders.ru.nl [mailto:fieldtrip-
> bounces at donders.ru.nl] On Behalf Of Matthew Davidson
> Sent: vrijdag 18 februari 2011 2:32
> To: fieldtrip at donders.ru.nl
> Subject: [FieldTrip] Single-subject Monte Carlo PLV or WPLI test?
> 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
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