eelbrain.pipeline.MneExperiment.load_induced_stc¶
-
MneExperiment.
load_induced_stc
(subjects=None, frequencies=None, n_cycles=None, pad=0.25, baseline=True, cat=None, morph=False, mask=False, vardef=None, 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 ifgroup
is specified).frequencies (
Union
[float
,Sequence
[float
],None
]) – Frequencies for which to compute induced activity.n_cycles (
Union
[float
,Sequence
[float
],None
]) – 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 (
Union
[bool
,Tuple
[Optional
[float
],Optional
[float
]]]) – Baseline for the epochs,True
to use the epoch’s baseline specification (default).cat (
Optional
[Sequence
[Union
[str
,Tuple
[str
, …]]]]) – Only load data for these cells (cells of model).morph (
bool
) – Morph the source estimates to the common_brain (default False).mask (
Union
[bool
,str
]) – Discard data that is labelledunknown
by the parcellation. Parcellation name (str
) to specify a parcellation,True
to use the state-parc` state parameter. Only applies whenndvar=True
, defaultFalse
.vardef (
Optional
[str
]) – Name of a test defining additional variables.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