mne.simulation.simulate_evoked(fwd, stc, info, cov, snr=3.0, tmin=None, tmax=None, iir_filter=None, random_state=None, verbose=None)

Generate noisy evoked data


No projections from info will be present in the output evoked. You can use e.g. evoked.add_proj or evoked.add_eeg_average_proj to add them afterward as necessary.


fwd : Forward

a forward solution.

stc : SourceEstimate object

The source time courses.

info : dict

Measurement info to generate the evoked.

cov : Covariance object

The noise covariance.

snr : float

signal to noise ratio in dB. It corresponds to 10 * log10( var(signal) / var(noise) ).

tmin : float | None

start of time interval to estimate SNR. If None first time point is used.

tmax : float | None

start of time interval to estimate SNR. If None last time point is used.

iir_filter : None | array

IIR filter coefficients (denominator) e.g. [1, -1, 0.2].

random_state : None | int | np.random.RandomState

To specify the random generator state.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose).


evoked : Evoked object

The simulated evoked data


New in version 0.10.0.