Compute spatial resolution metrics for linear solvers.
array
, shape (n_orient * n_vertices, n_vertices)The resolution matrix. If not a square matrix and if the number of rows is a multiple of number of columns (e.g. free or loose orientations), then the Euclidean length per source location is computed (e.g. if inverse operator with free orientations was applied to forward solution with fixed orientations).
SourceSpaces
Source space object from forward or inverse operator.
Whether to compute metrics for columns (point-spread functions, PSFs) or rows (cross-talk functions, CTFs) of the resolution matrix.
str
The resolution metric to compute. Allowed options are:
Localization-based metrics:
'peak_err'
Peak localization error (PLE), Euclidean distance
between peak and true source location.
'cog_err'
Centre-of-gravity localisation error (CoG), Euclidean
distance between CoG and true source location.
Spatial-extent-based metrics:
Amplitude-based metrics:
'peak_amp'
Ratio between absolute maximum amplitudes of peaks
per location and maximum peak across locations.
'sum_amp'
Ratio between sums of absolute amplitudes.
float
Amplitude fraction threshold for spatial extent metric ‘maxrad_ext’. Defaults to 0.5.
str
| int
| None
Control verbosity of the logging output. If None
, use the default
verbosity level. See the logging documentation and
mne.verbose()
for details. Should only be passed as a keyword
argument.
SourceEstimate
The resolution metric.
Notes
New in version 0.20.
References
mne.minimum_norm.resolution_metrics
#Compute spatial resolution metrics in source space
Compute spatial resolution metrics to compare MEG with EEG+MEG