Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.

fetch_atlas_pauli_2017

nilearn.datasets.fetch_atlas_pauli_2017(atlas_type='probabilistic', data_dir=None, verbose=1)[source]

Download the Pauli et al. (2017) atlas.

For more information, see the dataset description.

Parameters:
atlas_type{‘probabilistic’, ‘deterministic’}, default=’probabilistic’

Which type of the atlas should be download. This can be ‘probabilistic’ for the Probabilistic atlas, or ‘deterministic’ for the Deterministic atlas.

data_dirpathlib.Path or str or None, optional

Path where data should be downloaded. By default, files are downloaded in a nilearn_data folder in the home directory of the user. See also nilearn.datasets.utils.get_data_dirs.

verbosebool or int, default=1

Verbosity level (0 or False means no message).

Returns:
datasklearn.utils.Bunch

Dictionary-like object, contains:

  • atlas_type: str. Type of atlas. See Probabilistic atlas and Deterministic atlas.

  • labels: list of str. List of the names of the regions. The list contains values for both probabilistic and deterministic types.

  • lut: pandas.DataFrame. Act as a look up table (lut) with at least columns ‘index’ and ‘name’. Formatted according to ‘dseg.tsv’ format from BIDS.

  • maps: str. Full path to nifti file. If atlas_type='probabilistic', the image shape is (193, 229, 193, 16). If atlas_type='deterministic' the image shape is (198, 263, 212), and values are indices in the list of labels (integers from 0 to 16).

  • template: str. The standardized space of analysis in which the data is provided.

Notes

If the dataset files are already present in the user’s Nilearn data directory, this fetcher will not re-download them. To force a fresh download, you can remove the existing dataset folder from your local Nilearn data directory.

For more details on how Nilearn stores datasets.