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.

nilearn.datasets.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).

See Allen et al.[1].

The provided images are in MNI152 space.

Parameters:
data_dirpathlib.Path or str, 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, 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.

verboseint, default=1

Verbosity level (0 means no message).

Returns:
datasklearn.utils.Bunch

Dictionary-like object, keys are:

  • ‘maps’: str, path to nifti file containing the T-maps of all 75 unthresholded components. The image has shape (53, 63, 46, 75).

  • ‘rsn28’: str, path to nifti file containing the T-maps of 28 RSNs included in Allen et al.[1]. The image has shape (53, 63, 46, 28).

  • ‘networks’: list of list of str, list containing the names for the 28 RSNs.

  • ‘rsn_indices’: list of tuple, each tuple is a (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:

    # Should return [46, 64, 67, 48, 39, 59]
dict(data.rsn_indices)["Visual"]

  • ‘comps’: str, path to nifti file containing the aggregate ICA components.

  • ‘description’: str, description of the dataset.

Notes

License: unknown

See https://trendscenter.org/data/ for more information on this dataset.

References

Examples using nilearn.datasets.fetch_atlas_allen_2011

Visualizing 4D probabilistic atlas maps

Visualizing 4D probabilistic atlas maps