eelbrain.pipeline.MneExperiment.load_evoked

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

Load a Dataset with the evoked responses for each subject.

Parameters:
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

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 of cell-names

Only load data for these cells (cells of model).

decim : int

Data decimation factor (the default is the factor specified in the epoch definition).

data_raw : bool

Keep the mne.io.Raw instance in ds.info['raw'] (default False).

vardef : str

Name of a test defining additional variables.

data : str

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

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Applicable State Parameters: