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_allen_2011

nilearn.datasets.fetch_atlas_allen_2011(data_dir=None, url=None, resume=True, verbose=1)[source]

Download and return file names for the Allen and MIALAB ICA Probabilistic atlas (dated 2011).

For more information see the dataset description.

Parameters:
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.

urlstr or None, default=None

URL of file to download. Override download URL. Used for test only (or if you setup a mirror of the data).

resumebool, default=True

Whether to resume download of a partly-downloaded file.

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.

  • comps: str. Full path to 4D nifti file containing the aggregate ICA components.

  • maps: str. Full path to 4D nifti file containing T-maps of all 75 unthresholded components. The image has shape (53, 63, 46, 75).

  • networks: list of list of str. Names for the 28 resting state networks.

  • rsn28: str. Full path to 4D nifti file containing the 28 resting state networks from Allen et al 2011. The image has shape (53, 63, 46, 28).

  • rsn_indices: list of tuple of (str, list of int). This maps the network names to the map indices. For example, the map indices for the ‘Visual’ network can be obtained with dict(data.rsn_indices)['Visual]

  • 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.

Examples using nilearn.datasets.fetch_atlas_allen_2011

Visualizing 4D probabilistic atlas maps

Visualizing 4D probabilistic atlas maps