FieldTrip

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

  FT_SPIKE_XCORR computes the cross-correlation histogram and shift predictor.
 
  Use as
    [xcorr] = ft_spike_xcorr(cfg,data)
 
  The input SPIKE should be organised as the spike or the raw datatype, obtained from
  FT_SPIKE_MAKETRIALS or FT_PREPROCESSING (in that case, conversion is done
  within the function)
 
  Configurations options for xcorr general:
    cfg.maxlag           = number in seconds, indicating the maximum lag for the
                           cross-correlation function in sec (default = 0.1 sec).
    cfg.biased           = 'yes' or 'no' (default). If 'no', we scale the
                           cross-correlogram by M/(M-abs(lags)), where M = 2*N -1 with N
                           the length of the data segment. Although this scaling reduces the
                           bias, it can give a higher variance which might be more
                           problematic in some cases.
    cfg.shiftpredictor   = 'no' (default) or 'yes'. The shift-predictor is
    calculated from
                           channel x in every trial to the channel y in the previous
                           trial. If two channels are independent, then the shift
                           predictor should give the same correlogram as the raw
                           correlogram calculated from the same trials.
                           Typically, the shift predictor is subtracted from the
                           correlogram.
    cfg.outputunit       = 'proportion' (value in each bin indicates proportion of occurence)
                           'center' (values are scaled to center value which is set to 1)
                           'raw' (default) unnormalized crosscorrelogram.
 
    cfg.binsize          = [binsize] in sec (default = 0.001 sec).
 
  Configuration options of channel selection & checking, latency and trial selection:
    cfg.channelcmb       = Mx2 cell-array with selection of channel pairs (default = {'all' 'all'}),
                           see FT_CHANNELCOMBINATION for details
    cfg.latency          = [begin end] in seconds, 'max' (default), 'min', 'prestim'(t<=0), or
                           'poststim' (t>=0).%
    cfg.vartriallen      = 'yes' (default) or 'no'.
                           If 'yes' - accept variable trial lengths and use all available trials
                           and the samples in every trial.
                           If 'no'  - only select those trials that fully cover the window as
                           specified by cfg.latency and discard those trials that do not.
    cfg.trials           = numeric selection of trials (default = 'all')
    cfg.keeptrials       = 'yes' or 'no' (default)
 
  A peak at a negative lag for X.xcorr(:,chan1,chan2) means that chan1 is
  leading chan2. Thus, a negative lag represents a spike in the second
  dimension of X.xcorr before the channel in the third dimension of
  X.xcorr.
 
  Variable trial length is controlled by the option cfg.vartriallen. If
  cfg.vartriallen = 'yes', all trials are selected that have a minimum
  overlap with the latency window of cfg.maxlag. However, the shift
  predictor calculation demands that following trials have the same amount
  of data, otherwise, it does not control for rate non-stationarities. If
  cfg.vartriallen = 'yes', all trials should fall in the latency window,
  otherwise we do not compute the shift predictor.
 
  Output:
    xcorr.xcorr            = (2*nlags+1)-by-nchans-by-nchans cross correlation histogram
    xcorr.lags             = (2*nlags + 1) vector with lags in seconds.
    xcorr.shiftpredictor   = (2*nlags+1)-by-nchans-by-nchans shift predictor.
    xcorr.dimord
    xcorr.trial            = (2*nlags + 1)-by-ntrials-by-nchans-by-nchans with single
                             trials.
    xcorr.label            = corresponding labels to channels in xcorr.xcorr
    xcorr.cfg              = configurations used in this function.