eelbrain.pipeline.RawICA¶
-
class
eelbrain.pipeline.
RawICA
(source, session, method='extended-infomax', random_state=0, cache=False, **kwargs)¶ ICA raw pipe
Parameters: - source : str
Name of the raw pipe to use for input data.
- session : str | sequence of str
Session(s) to use for estimating ICA components.
- method : str
Method for ICA decomposition (default:
'extended-infomax'
; seemne.preprocessing.ICA
).- random_state : int
Set the random state for ICA decomposition to make results reproducible (default 0, see
mne.preprocessing.ICA
).- cache : bool
Cache the resulting raw files (default False).
- …
Additional parameters for
mne.preprocessing.ICA
.
See also
Notes
This preprocessing step estimates one set of ICA components per subject, using the data specified in the
session
parameter. The selected components are then removed from all data sessions during this preprocessing step, regardless of whether they were used to estimate the components or not.Use
make_ica_selection()
for each subject to select ICA components that should be removed. The arguments to that function determine what data is used to visualize the component time courses. For example, to determine which components load strongly on empty room data, usee.make_ica_selection(session='emptyroom')
(assuming an'emptyroom'
session is present).This step merges bad channels from all sessions.