mne_connectivity.make_signals_in_freq_bands#

mne_connectivity.make_signals_in_freq_bands(n_seeds, n_targets, freq_band, *, n_epochs=10, duration=None, n_times=None, sfreq=100.0, trans_bandwidth=1.0, snr=0.7, connection_delay=None, connection_time=None, window_alpha=0.5, tmin=0.0, ch_names=None, ch_types='eeg', rng_seed=None)[source]#

Simulate signals interacting in a given frequency band.

Parameters:

n_seedsint: Number of seed channels to simulate.
n_targetsint: Number of target channels to simulate.
freq_bandtuple of float: Frequency band where the connectivity should be simulated, where the first entry corresponds to the lower frequency, and the second entry to the higher frequency.
n_epochsint (default 10): Number of epochs in the simulated data.
durationfloat (default None): Duration of each epoch, in seconds.

Added in version 0.9.
n_timesint (default None): Number of timepoints in each epoch of the simulated data. If n_times=None and duration=None, 200 samples are used, and the unit of connection_delay is samples. If n_times=None and duration!=None, epoch length is determined by duration and the unit of connection_delay is seconds.

Deprecated since version 0.9: n_times is deprecated and will be removed in 1.0. Use duration instead to specify epoch length in seconds.
sfreqfloat (default 100.0): Sampling frequency of the simulated data, in Hz.
trans_bandwidthfloat (default 1.0): Transition bandwidth of the filter to apply to isolate activity in freq_band, in Hz. These are passed to the l_bandwidth and h_bandwidth keyword arguments in mne.filter.create_filter().
snrfloat (default 0.7): Signal-to-noise ratio of the simulated data in the range [0, 1].
connection_delayint | float (default None): Connectivity delay between the seeds and targets. If n_times is specified, the unit is samples, and the default (None) is 5 samples. If duration is specified, the unit is seconds, and the default (None) is 0.05 seconds. If > 0, the target data is a delayed form of the seed data. If < 0, the seed data is a delayed form of the target data. The absolute value must be less than duration.
connection_timetuple of float or None | None (default None): Start and end times at which the interaction occurs in each epoch, in seconds. First entry must be greater than tmin, last entry must be less than duration + tmin. If a given entry is None, it will be substituted for tmin or duration + tmin, as appropriate. If None, the connectivity is simulated throughout the whole epoch.

Added in version 0.9.
window_alphafloat (default 0.5): Fraction of the Tukey window in the cosine tapered region, used to isolate the interaction to a given time in the epochs. Must be between 0 and 1. 0 is equivalent to a rectangular window. 1 is equivalent to a Hann window. Ignored if connection_time is None.

Added in version 0.9.
tminfloat (default 0.0): Earliest time of each epoch, in seconds. Does not affect the total duration of each epoch. E.g., if duration=2.0 and tmin=-0.5, epochs will have timepoints in the range [-0.5, 1.5] seconds.
ch_nameslist of str | None (default None): Names of the channels in the simulated data. If None, the channels are named according to their index and the frequency band of interaction. If specified, must be a list of n_seeds + n_targets channel names.
ch_typesstr | list of str (default 'eeg'): Types of the channels in the simulated data. Must be a recognised data channel type (see data channels). If specified as a list, must be a list of n_seeds + n_targets channel names.
rng_seedint | None (default None): Seed to use for the random number generator. If None, no seed is specified.

Returns:

epochsEpochsArray, shape (n_epochs, n_seeds + n_targets, n_times): The simulated data stored in an mne.EpochsArray object. The channels are arranged according to seeds, then targets.

Notes

Signals are simulated as a single source of activity in the given frequency band and projected into n_seeds + n_targets white noise channels.

By default, connectivity is simulated throughout the whole epoch. However, the interaction can be isolated to a given time range using the connection_time and window_alpha parameters, mimicking an evoked potential. E.g., to simulate a burst of activity with a 200 ms duration beginning at the start of each epoch:

epochs = make_signals_in_freq_bands(
    ...,
    duration=2.0,  # 2 second epochs
    tmin=-0.5,  # make first 500 ms a pre-trial period (optional)
    connection_time=(0.0, 0.2),  # burst from 0 to 200 ms
    window_alpha=0.5,  # isolate burst with 50% cosine-tapered Tukey window
)

Added in version 0.7.

Examples using `mne_connectivity.make_signals_in_freq_bands`#

Compute multivariate coherency/coherence

Comparison of coherency-based methods

Multivariate decomposition for efficient connectivity analysis

mne_connectivity.make_signals_in_freq_bands#

Examples using mne_connectivity.make_signals_in_freq_bands#

Examples using `mne_connectivity.make_signals_in_freq_bands`#