Note that this reference documentation is identical to the help that is displayed in Matlab when you type “help ft_timelockanalysis”.
FT_TIMELOCKANALYSIS computes the timelocked average ERP/ERF and computes the covariance matrix Use as [timelock] = ft_timelockanalysis(cfg, data) The data should be organised in a structure as obtained from the FT_PREPROCESSING function. The configuration should be according to cfg.channel = Nx1 cell-array with selection of channels (default = 'all'), see FT_CHANNELSELECTION for details cfg.trials = 'all' or a selection given as a 1xN vector (default = 'all') cfg.covariance = 'no' or 'yes' (default = 'no') cfg.covariancewindow = 'prestim', 'poststim', 'all' or [begin end] (default = 'all') cfg.keeptrials = 'yes' or 'no', return individual trials or average (default = 'no') cfg.removemean = 'no' or 'yes' for covariance computation (default = 'yes') cfg.vartrllength = 0, 1 or 2 (see below) Depending on cfg.vartrllength, variable trials and missing values are treated differently: 0 - do not accept variable length trials [default] 1 - accept variable length trials, but only take those trials in which data is present in both the average and the covariance window 2 - accept variable length trials, use all available trials the available samples in every trial will be used for the average and covariance computation. Missing values are replaced by NaN and are not included in the computation. To facilitate data-handling and distributed computing you can use cfg.inputfile = ... cfg.outputfile = ... If you specify one of these (or both) the input data will be read from a *.mat file on disk and/or the output data will be written to a *.mat file. These mat files should contain only a single variable, corresponding with the input/output structure. See also FT_TIMELOCKGRANDAVERAGE, FT_TIMELOCKSTATISTICS