[Mne_analysis] Negative Weighted Phase Lag Index Values

[Eric Larson]

Fig1C shows the individual vectors and how they're weighted -- I was
looking at Eq.8 which defines WPLI, and the paragraph that followed where
they state that 0 ≤ Φ ≤ 1 holds (due to the absolute value operations in
the numerator and denominator). But maybe there is more to it or you don't
need to take the absolute value of the expectation in the numerator, in
which case it could be -1 ≤ Φ ≤ 1, is that what you have in mind...?

Eric


On Wed, Jun 14, 2017 at 3:13 PM, Andrea Brovelli <
andrea.brovelli at univ-amu.fr> wrote:

> Dear all,
>
> I don't know the implementation in MNE, but, as far as I know, the WPLI
> ranges between between -1 and 1 (see Fig. 1C in Vinck, Neuroimage 2011).
> The same is for the imaginary coherence (Nolte, Clin Neurophysiol 2004).
>
> The strength of phase-synchronization can be indexed by the magnitude (or
> squared value) of the WPLI.
>
> bye
>
> Andrea
>
>
>
>
> Le 14-Jun-17 à 7:51 PM, Eric Larson a écrit :
>
> Yes it looks like WPLI should be bounded by 0 and 1. Can you open an MNE
> issue so we can look into it further?
>
> Eric
>
>
> On Wed, Jun 14, 2017 at 1:28 PM, Stout, Jeffrey <jstout at mcw.edu> wrote:
>
>> We are running analyses on resting state MEG data and we are finding
>> negative values in the weighted phase lag index (wpli) measure.  We have
>> also run this data using the phase lag index (PLI) measure and do not see
>> any values below zero.  I thought that both the PLI and WPLI should be
>> defined from 0 to 1.  Although the negative values tend to be small, we are
>> seeing this across many subjects.
>>
>>
>>
>> wpli=np.load('connmat_wpli2_debiased13_30hz_run1.npy')
>>
>>
>>
>> np.min(wpli), np.max(wpli)
>>
>> Out[22]: (-0.0048496421426467845, 0.14954351856205442)     <<<<<<<<< WPLI
>> minimum value below Zero
>>
>>
>>
>> pli=np.load('connmat_pli13_30hz_run1.npy')
>>
>>
>>
>> np.min(pli), np.max(pli)
>>
>> Out[24]: (0.0, 0.21375066880684856) <<<<<<<<< PLI minimum value equals
>> zero
>>
>>
>>
>>
>>
>> Is this a correct finding?  Any insight would be helpful.
>>
>>
>>
>>
>>
>> Thank you,
>>
>> Jeff Stout
>>
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