neuromaps.nulls.burt2018

neuromaps.nulls.burt2018(data, atlas='fsaverage', density='10k', parcellation=None, n_perm=1000, seed=None, distmat=None, n_proc=1, **kwargs)[source]

Generates null maps for data using method from [SN6]

Method uses a spatial auto-regressive model to estimate distance-dependent relationship of data and generates surrogate maps with similar properties

Parameters

  • data ((N,) array_like) – Input data from which to generate null maps

  • 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 surface mesh 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

  • distmat (tuple-of-str or os.PathLike, optional) – Filepaths to pre-computed (left, right) surface distance matrices. Providing this will cause atlas, density, and parcellation to be ignored. Default: None

  • kwargs (key-value pairs) – Other keyword arguments passed directly to the underlying null method generator

Returns

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

Return type

np.ndarray

References

SN6

Burt, J. B., Demirtaş, M., Eckner, W. J., Navejar, N. M., Ji, J. L., Martin, W. J., … & Murray, J. D. (2018). Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography. Nature Neuroscience, 21(9), 1251-1259.