mne.minimum_norm.cross_talk_function¶
-
mne.minimum_norm.
cross_talk_function
(inverse_operator, forward, labels, method='dSPM', lambda2=0.1111111111111111, signed=False, mode='mean', n_svd_comp=1, use_cps=True, verbose=None)[source]¶ Compute cross-talk functions (CTFs) for linear estimators.
Compute cross-talk functions (CTF) in labels for a combination of inverse operator and forward solution. CTFs are computed for test sources that are perpendicular to cortical surface.
- Parameters
- inverse_operatorinstance of
InverseOperator
Inverse operator.
- forward
dict
Forward solution. Note: (Bad) channels not included in forward solution will not be used in CTF computation.
- labels
list
ofLabel
Labels for which CTFs shall be computed.
- method‘MNE’ | ‘dSPM’ | ‘sLORETA’ | ‘eLORETA’
Inverse method for which CTFs shall be computed.
- lambda2
float
The regularization parameter.
- signedbool
If True, CTFs will be written as signed source estimates. If False, absolute (unsigned) values will be written
- mode‘mean’ | ‘sum’ | ‘svd’
CTFs can be computed for different summary measures with labels: ‘sum’ or ‘mean’: sum or means of sub-inverses for labels This corresponds to situations where labels can be assumed to be homogeneously activated. ‘svd’: SVD components of sub-inverses for labels This is better suited for situations where activation patterns are assumed to be more variable. “sub-inverse” is the part of the inverse matrix that belongs to vertices within individual labels.
- n_svd_comp
int
Number of SVD components for which CTFs will be computed and output (irrelevant for ‘sum’ and ‘mean’). Explained variances within sub-inverses are shown in screen output.
- use_cps
None
| bool (defaultTrue
) Whether to use cortical patch statistics to define normal orientations. Only used when surf_ori and/or force_fixed are True.
- verbosebool,
str
,int
, orNone
If not None, override default verbose level (see
mne.verbose()
and Logging documentation for more).
- inverse_operatorinstance of
- Returns
- stc_ctf
SourceEstimate
The CTFs for the specified labels. If mode=’svd’: n_svd_comp components per label are created (i.e. n_svd_comp successive time points in mne_analyze) The last sample is the summed CTF across all labels.
- stc_ctf