Difference between |Imag(C)| and phase locking value

najins · February 6, 2020, 8:01pm

What's the difference between |Imag(C)| and phase locking value?

Francois · February 10, 2020, 1:55pm

The new imaginary coherence measure is described here:

brainstorm-tools/brainstorm3/blob/master/toolbox/connectivity/bst_cohn.m#L23


%    - isSymmetric   : If 1, use an optimized method for symmetrical matrices

%    - ImagingKernel : If not empty, calculate the coherence at the source level

%    - waitMax       : Increase of the progress bar during the execution of this function

%

% CohMeasure (Definitions):

%     In Late 2019, the fft-based coherence functions were updated. The

%     lagged and Imaginary coherence have different definitions among two

%     versions. The recent changes are set as default. Please consider this

%     if you want to reproduce your former analyses. 

%     

%     Gxy:  cross-spectral density between x and y

%     Gxx:  autospectral density of x

%     Gyy:  autospectral density of y

%     Coherence function (C)            : Gxy/sqrt(Gxx*Gyy)

%     Magnitude-squared Coherence (MSC) : |C|^2 = |Gxy|^2/(Gxx*Gyy) = Gxy*conj(Gxy)/(Gxx*Gyy) 

%   

%     ============ 'icohere2019', 'lcohere2019' =============

%     Imaginary Coherence (IC)          : abs(imag(C))               

%     Lagged Coherence (LC)             : abs(imag(C))/sqrt(1-real(C)^2)

%

%     ========= 'icohere' (before 2019) =========

The phase locking value is computed here:

github.com

brainstorm-tools/brainstorm3/blob/master/toolbox/connectivity/bst_connectivity.m#L493


bst_progress('text', sprintf('Calculating: PLV [%dx%d]...', size(sInputA.Data,1), size(sInputB.Data,1)));

Comment = 'PLV: ';

% Get frequency bands

nFreqBands = size(OPTIONS.Freqs, 1);

BandBounds = process_tf_bands('GetBounds', OPTIONS.Freqs);



% ===== IMPLEMENTATION G.DUMAS =====

% Intitialize returned matrix

R = zeros(size(sInputA.Data,1), size(sInputB.Data,1), nFreqBands);

% Loop on each frequency band

for iBand = 1:nFreqBands

    % Band-pass filter in one frequency band + Apply Hilbert transform

    if isConnNN

        DataAband = process_bandpass('Compute', sInputA.Data, sfreq, BandBounds(iBand,1), BandBounds(iBand,2), 'bst-hfilter-2019', OPTIONS.isMirror);

        HA = hilbert_fcn(DataAband')';

        HB = HA;

    else

        DataAband = process_bandpass('Compute', sInputA.Data, sfreq, BandBounds(iBand,1), BandBounds(iBand,2), 'bst-hfilter-2019', OPTIONS.isMirror);

        DataBband = process_bandpass('Compute', sInputB.Data, sfreq, BandBounds(iBand,1), BandBounds(iBand,2), 'bst-hfilter-2019', OPTIONS.isMirror);

        HA = hilbert_fcn(DataAband')';

        HB = hilbert_fcn(DataBband')';

These two measures are presented in the draft of the future connectivity tutorial:
https://neuroimage.usc.edu/brainstorm/Tutorials/Connectivity

@hossein27en: anything to add?