MneExperiment.load_evoked(subjects=None, baseline=False, ndvar=True, cat=None, samplingrate=None, decim=None, data_raw=False, vardef=None, data='sensor', **state)

Load a Dataset with the evoked responses for each subject.

  • subjects (str | 1 | -1) – Subject(s) for which to load data. Can be a single subject name or a group name such as 'all'. 1 to use the current subject; -1 for the current group. Default is current subject (or group if group is specified).

  • baseline (bool | Tuple[float | None, float | None]) – Apply baseline correction using this period. True to use the epoch’s baseline specification. The default is to not apply baseline correction.

  • ndvar (bool | 2) – Convert the mne.Evoked objects to an NDVar (the name in the Dataset is 'meg' or 'eeg'). With ndvar=False, the mne.Evoked objects are added as 'evoked'. 2 to add both.

  • cat (Sequence[str | Tuple[str, ...]]) – Only load data for these cells (cells of model).

  • samplingrate (int) – Samplingrate in Hz for the analysis (default is specified in epoch definition).

  • decim (int) – Data decimation factor (alternative to samplingrate).

  • data_raw (bool) – Keep the instance in['raw'] (default False).

  • vardef (str) – Name of a test defining additional variables.

  • data (str | TestDims) – Data to load; ‘sensor’ to load all sensor data (default); ‘sensor.rms’ to return RMS over sensors. Only applies to NDVar output.

  • ...

    Applicable State Parameters:


Channel interpolation: Bad channels are always interpolated. When loading data for a single subject, bad channels are marked as bad/excluded. When loading group level data, datasets are merged using interpolated data.