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_talairach

nilearn.datasets.fetch_atlas_talairach(level_name, data_dir=None, verbose=1)[source]

Download the Talairach Deterministic atlas.

For more information, see the dataset description.

Added in Nilearn 0.4.0.

Parameters:
level_name{‘hemisphere’, ‘lobe’, ‘gyrus’, ‘tissue’, ‘ba’}

Which level of the atlas to use: the hemisphere, the lobe, the gyrus, the tissue type or the Brodmann area.

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 starts with ‘Background’ (region ID 0 in the image).

  • 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: nibabel.nifti1.Nifti1Image. Nifti1Image containing the label image with shape (141, 172, 110) and contains consecutive integer values from 0 to the number of regions, which are indices in the list of labels.

  • 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.