neuromaps.nulls.alexander_bloch

neuromaps.nulls.alexander_bloch(data, atlas='fsaverage', density='10k', parcellation=None, n_perm=1000, seed=None, spins=None, surfaces=None)[source]

Generate null maps from data using method from [SN1].

Method projects data to a spherical surface and uses arbitrary rotations to generate null distribution. If data are parcellated then parcel centroids are projected to surface and parcels are reassigned based on minimum distances.

Parameters:

  • data (array_like or path_like or giimg_like or tuple) – Input data from which to generate null maps. If None is provided then the resampling array will be returned instead. When a parcellation is provided, the data must be parcellated and array-like. Otherwise, the data must be a surface-based image (giimg_like, e.g. nib.GiftiImage) or a path-like object (str or os.PathLike) pointing to an image file.

  • atlas ({'fsLR', 'fsaverage', 'civet'}, optional) – Name of surface atlas on which data are defined. Default: ‘fsaverage’

  • density (str, optional) – Density of surface mesh on which data are defined. Must be compatible with specified atlas. Default: ‘10k’

  • parcellation (tuple-of-str or os.PathLike, optional) – Filepaths to parcellation images ([left, right] hemisphere) mapping data to atlas specified by atlas and density. Should only be supplied if data represents a parcellated null map. Default: None

  • n_perm (int, optional) – Number of null maps or permutations to generate. Default: 1000

  • seed ({int, np.random.RandomState instance, None}, optional) – Seed for random number generation. Default: None

  • spins (array_like or str or os.PathLike) – Filepath to or pre-loaded resampling array. If not specified spins are generated. Default: None

  • surfaces (tuple-of-str or os.PathLike, optional) – Instead of specifying atlas and density this specifies the surface files on which data are defined. Providing this will override arguments supplied to atlas and density. Default: None

Returns:

nulls – Generated null distribution, where each column represents a unique null map

Return type:

np.ndarray

References

[SN1]

Alexander-Bloch, A., Shou, H., Liu, S., Satterthwaite, T. D., Glahn, D. C., Shinohara, R. T., Vandekar, S. N., & Raznahan, A. (2018). On testing for spatial correspondence between maps of human brain structure and function. NeuroImage, 178, 540-51.