[Mne_analysis] Negative Weighted Phase Lag Index Values
CCUSHING1 at mgh.harvard.edu
Thu Jun 15 11:20:35 EDT 2017
I'm not sure whether to respond here or to that Digest email that just got sent out, but Jeff appears to also be using the 'wpli2_debiased' method, according to the chunks of code that just got sent out:
" con_methods = ['coh', 'pli', 'wpli2_debiased'] "
And Eric seems to be correct that these values can indeed be negative. If you look at Fig. 12 of Vinck et. al 2011, their color mapping spans from -0.2 to 0.6, with the two bias measure (unbiased PLI2 and debased WPLI2) both appearing to reach negative values compared to the direct PLI2. So, if Jeff is truly using 'wpli2_debiased' as his method just as I am (as the code suggests), then there should be no bug.
From: mne_analysis-bounces at nmr.mgh.harvard.edu [mne_analysis-bounces at nmr.mgh.harvard.edu] on behalf of Andrea Brovelli [andrea.brovelli at univ-amu.fr]
Sent: Thursday, June 15, 2017 2:49 AM
To: mne_analysis at nmr.mgh.harvard.edu
Subject: Re: [Mne_analysis] Negative Weighted Phase Lag Index Values
Suggestion: in Fieldtrip, the WPLI is implemented in its signed version, it is not the eq.8 of Vinck' paper, which is bounded [0, 1].
The estimator is (line 73 in ft_connectivity_wpli.m<https://github.com/fieldtrip/fieldtrip/blob/master/connectivity/ft_connectivity_wpli.m> ):
Maybe the MNE code got inspiration from it.
Le 14-Jun-17 à 10:48 PM, Eric Larson a écrit :
this also occurs when computing the debiased squared wpli, where there should undoubtedly be no negative values (unless the debiasing does something strange that I'm not aware of), just FYI.
>From what I recall the debiasing can indeed produce (generally small) negative values, so that at least I would expect. From Vinck et al., 2011:
If the WPLI exceeds the PLI, then the debiased WPLI-square estimator will be negatively biased for small sample sizes.
The WPLI, however, doesn't have this characteristic, and from what I've seen in a brief look at the MNE code, I'm not sure where it could come from (based on where we use abs()). So a minimal example would help us track it down.
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