neuromaps.nulls.vasa
- neuromaps.nulls.vasa(data, atlas='fsaverage', density='10k', parcellation=None, n_perm=1000, seed=None, spins=None, surfaces=None)[source]
Generate null maps for parcellated data using method from [SN2].
Method projects parcels to a spherical surface and uses arbitrary rotations with iterative reassignments to generate null distribution. All nulls are “perfect” permutations of the input data (at the slight expense of spatial topology)
- Parameters:
data ((N,) array_like) – Input data from which to generate null maps. The data must be parcellated and array-like. If None is provided then the resampling array will be returned instead.
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
[SN2]Váša, F., Seidlitz, J., Romero-Garcia, R., Whitaker, K. J., Rosenthal, G., Vértes, P. E., … & Jones, P. B. (2018). Adolescent tuning of association cortex in human structural brain networks. Cerebral Cortex, 28(1), 281-294.