eelbrain.datasets.simulate_erp

eelbrain.datasets.simulate_erp(n_trials=80, seed=0, snr=0.2, sensor=None, time=None, short_long=False)

Simulate event-related EEG data

Parameters:
  • n_trials (int) – Number of trials (default 100).

  • seed (int) – Random seed.

  • snr (float) – Signal-to-noise ratio.

  • sensor (Sensor) – Sensor dimension.

  • time (UTS) – Time dimension.

  • short_long (bool) – Create bimodal distribution of word length for categorial analysis.

Return type:

Dataset

Examples

Compare with kiloword:

ys = datasets.simulate_erp()['eeg']
ys -= ys.mean(sensor=['M1', 'M2'])
import mne
path = mne.datasets.kiloword.data_path()
y = load.mne.epochs_ndvar(path + '/kword_metadata-epo.fif')
plot.TopoButterfly([y, ys])