mne.sensitivity_map#

mne.sensitivity_map(fwd, projs=None, ch_type='grad', mode='fixed', exclude=(), *, verbose=None)[source]#

Compute sensitivity map.

Such maps are used to know how much sources are visible by a type of sensor, and how much projections shadow some sources.

Parameters:
fwdForward

The forward operator.

projslist

List of projection vectors.

ch_type'grad' | 'mag' | 'eeg'

The type of sensors to use.

mode'free' | 'fixed' | 'ratio' | 'radiality' | 'angle' | 'remaining' | 'dampening'

Which sensitivity quantity to compute:

  • ‘free’ : Maximum obtainable signal over all source orientations.

  • ‘fixed’ : Signal from sources constrained to be normal to the cortical surface.

  • ‘ratio’ : Ratio of ‘fixed’ sensitivity to the ‘free’ (maximum-over-orientations) sensitivity.

  • ‘radiality’ : Ratio of signal from sources normal to the cortex to the maximum signal among all orientations.

  • ‘angle’ : Subspace angle with the noise subspace.

  • ‘remaining’ : Fraction of signal remaining after the projection (e.g., after SSS/SSP).

  • ‘dampening’ : Fraction of signal dampening due to the projection.

excludelist of str | str

List of channels to exclude. If empty do not exclude any (default). If 'bads', exclude channels in fwd['info']['bads'].

verbosebool | 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.

Returns:
stcSourceEstimate | VolSourceEstimate

The sensitivity map as a SourceEstimate or VolSourceEstimate instance for visualization.

Notes

When mode is 'fixed' or 'free', the sensitivity map is normalized by its maximum value.

Examples using mne.sensitivity_map#

Display sensitivity maps for EEG and MEG sensors

Display sensitivity maps for EEG and MEG sensors

Use source space morphing

Use source space morphing

Sensitivity map of SSP projections

Sensitivity map of SSP projections