eelbrain.pipeline.Pipeline.load_induced_stc

Pipeline.load_induced_stc(subjects=None, frequencies=None, n_cycles=None, pad=0.25, baseline=True, cat=None, morph=False, decim=1, **state)

Morlet wavelet induced power and phase in source space.

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).

• frequencies (float | Sequence[float]) – Frequencies for which to compute induced activity.

• n_cycles (float | Sequence[float]) – Number of cycles in each wavelet. Fixed number or one per frequency.

• pad (float) – Pad the epochs data to avoid edge effects in wavelet representation (specified in seconds; default 0.250).

• baseline (bool | tuple[float | None, float | None]) – Baseline for the epochs, True to use the epoch’s baseline specification (default).

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

• morph (bool) – Morph the source estimates to the common_brain (default False).

• decim (int) – Decimate time-frequency representation (cumulative with epoch decimation factor).

• ... –

  Applicable State Parameters:

  • raw: preprocessing pipeline

  • epoch: which events to use and time window

  • rej (trial rejection): which trials to use

  • model: how to group trials into conditions

  • equalize_evoked_count: control number of trials per cell

  • cov: covariance matrix for inverse solution

  • src: source space

  • inv: inverse solution

Return type:

Dataset