[Mne_analysis] Negative Weighted Phase Lag Index Values

[Eric Larson]

Jeff,

When you get a chance, could you try to share some data (as small as
possible) and a small code snippet (using coherence-computing routines)
that show this problem to the related MNE issue I opened
<https://github.com/mne-tools/mne-python/issues/4319>?

Eric


On Wed, Jun 14, 2017 at 3:22 PM, Eric Larson <larson.eric.d at gmail.com>
wrote:

> 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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