MneExperiment.load_epochs_stc(subjects=None, baseline=True, src_baseline=False, cat=None, keep_epochs=False, morph=None, mask=False, data_raw=False, vardef=None, samplingrate=None, decim=None, pad=0, ndvar=True, reject=True, **state)

Load a Dataset with stcs for single epochs

  • 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). Warning: loading single trial data for multiple subjects at once uses a lot of memory, which can lead to a periodically unresponsive terminal).

  • baseline (bool | Tuple[float | None, float | None]) – Apply baseline correction using this period in sensor space. True to use the epoch’s baseline specification (default).

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

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

  • keep_epochs (bool | 'ndvar' | 'both') – Keep the sensor space data in the Dataset that is returned (default False; True to keep mne.Epochs object; 'ndvar' to keep NDVar; 'both' to keep both).

  • morph (bool) – Morph the source estimates to the common brain (default False, except when loading multiple subjects and ndvar=True).

  • mask (bool | str) – Discard data that is labelled unknown by the parcellation. Parcellation name (str) to specify a parcellation, True to use the parc/mask (parcellations) state parameter. Only applies when ndvar=True, default False.

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

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

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

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

  • pad (float) – Pad the epoch’s data by extending tmin and tmax (specify pad time in seconds).

  • ndvar (bool) – Add the source estimates as NDVar named “src” instead of a list of mne.SourceEstimate objects named “stc” (default True).

  • reject (bool | 'keep') – Reject bad trials. If True (default), bad trials are removed from the Dataset. Set to False to ignore the trial rejection. Set reject='keep' to load the rejection (added it to the events as 'accept' variable), but keep bad trails.

  • ...

    Applicable State Parameters:

    • raw: preprocessing pipeline

    • epoch: which events to use and time window

    • rej (trial rejection): which trials to use

    • cov: covariance matrix for inverse solution

    • src: source space

    • inv: inverse solution


epochs_dataset – Dataset containing single trial data (epochs).

Return type: