ffrprep.analysis.rms_snr¶

ffrprep.analysis.rms_snr(evoked, response_lower=0.1, response_upper=0.2)[source]¶

Compute RMS-based signal-to-noise ratio (SNR) for an Evoked response.

Parameters:

evoked (mne.Evoked) – Evoked object containing averaged M/EEG data.
response_lower (float, default=0.100) – Start time (in seconds) of the response window, relative to the Evoked time axis.
response_upper (float, default=0.200) – End time (in seconds) of the response window, relative to the Evoked time axis.

Returns:

rms_snr – The RMS SNR computed as: RMS(response window) / RMS(baseline window) for the first channel in evoked.data.

Return type:

float

Examples

Compute RMS SNR for a 100-200 ms response window

>>> snr = rms_snr(evoked, response_lower=0.100, response_upper=0.200)
>>> float(np.round(snr, 3))
3.412