Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_connectivity_laggedcoherence”.

  FT_CONNECTIVITY_LAGGEDCOHERENCE performs time-resolved coherence analysis of
  oscillatory activity only, both within and between recording sites. This implements
  the method described in Fransen, Anne M. M, Van Ede, Freek, Maris, Eric (2015)
  Identifying oscillations on the basis of rhythmicity. NeuroImage 118: 256-267.
 
  Use as
    lcoh = ft_connectivityanalysis(cfg, freq)
  with cfg.method='laggedcoherence' or as
     lcoh = ft_connectivity_laggedcoherence(cfg, freq)
 
  The input data should be organised in a structure as obtained from FT_FREQANALYSIS
  and should contain the fields 'fourierspctrm' and 'time'. The timepoints must be
  chosen such that the desired cfg.lag/cfg.foi (lag in s) is an integer multiple of
  the time resolution in freqout.
 
  This function must be called separately for each frequency of interest. To analyse
  multiple frequencies, we advise the use of a for loop like this:
    cfg_F             = [];
    cfg_F.method      = 'wavelet';
    cfg_F.output      = 'fourier';
    cfg_F.width       = 3;
    cfg_F.keeptrials  = 'yes';
    cfg_LC            = [];
    cfg_LC.lag        = cfg_F.width;
    cfg_LC.method     = 'laggedcoherence';
    foi               = 1:1:100;
    fs                = data.fsample;
    for counter = 1:length(foi);
        cfg_F.foi     = foi(counter);
        cfg_LC.foi    = foi(counter);
        width         = cfg_F.width/cfg_F.foi;
        cfg_F.toi     = data.time{1}(1) + ceil(fs*width/2)/fs : ...   %from:
          cfg_LC.lag/cfg_F.foi : ...                     %in steps of size:
          data.time{1}(end) - ceil(fs*width/2)/fs;                     %to:
        freqout       = ft_freqanalysis(cfg_F,data);
        lcoh(counter) = ft_connectivityanalysis(cfg_LC,freqout);
    end
 
  The configuration structure cfg should contain:
    cfg.foi          =  frequency of interest (default=freqout.freq(1))
    cfg.lag          =  the number of periods between the onset of the time window
                        used for phase estimate 1 and the onset of the time window
                        for phase estimate 2 (the default cfg.lag is set to match the
                        time resolution in freqout). We recommend users to choose
                        cfg.lag such that it is larger or equal to the width of the
                        wavelet used for each Fourier transform in ft_freqanalysis
    cfg.output       =  'lcoh', or 'csd' (default='lcoh'). When the output
                        is set to 'csd', one can specify the channel combinations
                        between which to compute the lagged cross-spectra in
                        cfg.channelcmb
 
  To calculate lagged coherence values from the cross-spectra, do:
     abs(lcoh.laggedcrsspctrm)./sqrt(lcoh.powspctrm1.*lcoh.powspctrm2)
  where lcoh.powspctrm1 denotes power in the channels of the first
  column of cfg.channelcmb, and lcoh.powspctrm2 does the same for the
  channels in the second column of cfg.channelcmb. Note that the power
  is calculated for the same time windows that are used for calculating
  the lagged cross-spectra.
 
  Optional settings:
    cfg.timeresolved = 'yes' or 'no' (default='no'). If set to yes, lagged
                       coherence is calculated separately for each pair of timepoints
                       that is separated by cfg.lag
    cfg.nlags        = the lags in lcoh are the set of (1:1:nlags)*lag
                       (default = 1). Note that if cfg.timeresolved=='yes', then
                       cfg.nlags must be set to 1.
    cfg.channel      = Nx1 cell-array with selection of channels
                       (default = 'all'), see FT_CHANNELSELECTION for details
    cfg.channelcmb   = Mx2 cell-array with channel pairs, (default={'all','all'}),
                       see FT_CHANNELCOMBINATION for details
    cfg.autocmb      = 'yes' or 'no' (default='no'). Adds all auto-
                       combinations of cfg.channel to cfg.channelcmb
    cfg.trialsets    = cell array with per cell the set of trials over
                       which lcoh is calculated. Each cell must contain 'all' or a
                       1xN vector of trial indices. Default={'all'}. Note that this
                       differs from the required format of cfg.trials in e.g.
                       ft_connectivityanalysis.
 
  See also FT_CONNECTIVITYANALYSIS