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)

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 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, 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.

• ‘atlas_type’str

  Type of atlas. See Probabilistic atlas and Deterministic atlas.

• ‘template’str

  The standardized space of analysis in which the atlas results are provided. When known it should be a valid template name taken from the spaces described in the BIDS specification.

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.

License: unknown

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

References

[1] (1,2)

Elena Allen, Erik Erhardt, Eswar Damaraju, William Gruner, Judith Segall, Rogers Silva, Martin Havlicek, Srinivas Rachakonda, Jill Fries, Ravi Kalyanam, Andrew Michael, Arvind Caprihan, Jessica Turner, Tom Eichele, Steven Adelsheim, Angela Bryan, Juan Bustillo, Vincent Clark, Sarah Feldstein Ewing, Francesca Filbey, Corey Ford, Kent Hutchison, Rex Jung, Kent Kiehl, Piyadasa Kodituwakku, Yuko Komesu, Andrew Mayer, Godfrey Pearlson, John Phillips, Joseph Sadek, Michael Stevens, Ursina Teuscher, Robert Thoma, and Vince Calhoun. A baseline for the multivariate comparison of resting-state networks. Frontiers in Systems Neuroscience, 5:2, 2011. doi:10.3389/fnsys.2011.00002.

Examples using nilearn.datasets.fetch_atlas_allen_2011

Visualizing 4D probabilistic atlas maps

Visualizing 4D probabilistic atlas maps