mne_nirs.io.fold_landmark_specificity#

mne_nirs.io.fold_landmark_specificity(raw, landmark, fold_files=None, atlas='Juelich', interpolate=False)[source]#

Return the specificity of each channel to a specified brain landmark.

Parameters:
rawBaseRaw

The fNIRS data.

landmarkstr

Landmark of interest. Must be present in fOLD toolbox data file.

fold_fileslist | path-like | None

If None, will use the MNE_NIRS_FOLD_PATH config variable. If path-like, should be a path to a directory containing ‘10-10.xls’ and ‘10-5.xls’. If list, should be paths to the fold toolbox files. See the Notes section of fold_channel_specificity() for details.

atlasstr

Brain atlas to use.

interpolatebool

If the optimal source-detector pair is not found in the fOLD files False (default) will yield no results for that pairing, whereas True will use the next closest match. See Notes of mne_nirs.io.fold_channel_specificity() for an example.

Warning

The sensitivity profile can differ substantially for nearest neighbors, so use interpolate=True with caution.

Returns:
specarray

Specificity values for each channel to brain landmark.

Notes

Specificity values are provided by the fOLD toolbox [1] excel files. See the Notes section of fold_channel_specificity() for more details.

References

Examples using mne_nirs.io.fold_landmark_specificity#

Utilising Anatomical Information

Utilising Anatomical Information