FT_CONNECTIVITYSIMULATION
Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_connectivitysimulation”.
FT_CONNECTIVITYSIMULATION simulates channel-level time-series data with a specified connectivity structure. This function returns an output data structure that resembles the output of FT_PREPROCESSING. Use as [data] = ft_connectivitysimulation(cfg) where the configuration structure should contain: cfg.method = string, can be 'linear_mix', 'mvnrnd', 'ar', 'ar_reverse' (see below) cfg.nsignal = scalar, number of signals cfg.ntrials = scalar, number of trials cfg.triallength = in seconds cfg.fsample = in Hz Depending on the specific method that is selected, the configuration may also contain: Method 'linear_mix' implements a linear mixing with optional time shifts where the number of unobserved signals can be different from the number of observed signals Required cfg options: cfg.mix = matrix, [nsignal x number of unobserved signals] specifying the mixing from the unobserved signals to the observed signals, or = matrix, [nsignal x number of unobserved signals x number of samples] specifying the mixing from the unobserved signals to the observed signals which changes as a function of time within the trial = cell-arry, [1 x ntrials] with each cell a matrix as specified above, when a trial-specific mixing is required cfg.delay = matrix, [nsignal x number of unobserved signals] specifying the time shift (in samples) between the unobserved signals and the observed signals Optional cfg options: cfg.bpfilter = 'yes' (or 'no') cfg.bpfreq = [bplow bphigh] (default: [15 25]) cfg.demean = 'yes' (or 'no') cfg.baselinewindow = [begin end] in seconds, the default is the complete trial cfg.absnoise = scalar (default: 1), specifying the standard deviation of white noise superimposed on top of the simulated signals cfg.randomseed = 'yes' or a number or vector with the seed value (default = 'yes') Method 'mvnrnd' implements a linear mixing with optional timeshifts in where the number of unobserved signals is equal to the number of observed signals. This method used the MATLAB function mvnrnd. The implementation is a bit ad-hoc and experimental, so users are discouraged to apply it. The time shift occurs only after the linear mixing, so the effect of the parameters on the simulation is not really clear. This method will be disabled in the future. Required cfg options: cfg.covmat = covariance matrix between the signals cfg.delay = delay vector between the signals in samples Optional cfg options: cfg.bpfilter = 'yes' (or 'no') cfg.bpfreq = [bplow bphigh] (default: [15 25]) cfg.demean = 'yes' (or 'no') cfg.baselinewindow = [begin end] in seconds, the default is the complete trial cfg.absnoise = scalar (default: 1), specifying the standard deviation of white noise superimposed on top of the simulated signals Method 'ar' implements a multivariate autoregressive model to generate the data. Required cfg options: cfg.params = matrix, [nsignal x nsignal x number of lags] specifying the autoregressive coefficient parameters. A non-zero element at cfg.params(i,j,k) means a directional influence from signal j onto signal i (at lag k). cfg.noisecov = matrix, [nsignal x nsignal] specifying the covariance matrix of the innovation process Method 'ar_reverse' implements a multivariate autoregressive autoregressive model to generate the data, where the model coefficients are reverse-computed, based on the interaction pattern specified. Required cfg options: cfg.coupling = nxn matrix, specifying coupling strength, rows causing column cfg.delay = nxn matrix, specifying the delay, in seconds, from one signal's spectral component to the other signal, rows causing column cfg.ampl = nxn matrix, specifying the amplitude cfg.bpfreq = nxnx2 matrix, specifying the lower and upper frequencies of the bands that are transmitted, rows causing column The generated signals will have a spectrum that is 1/f + additional band-limited components, as specified in the cfg. See also FT_FREQSIMULATION, FT_DIPOLESIMULATION, FT_SPIKESIMULATION, FT_CONNECTIVITYANALYSIS