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_schaefer_2018

nilearn.datasets.fetch_atlas_schaefer_2018(n_rois=400, yeo_networks=7, resolution_mm=1, data_dir=None, base_url=None, resume=True, verbose=1)[source]

Download and return file names for the Schaefer 2018 parcellation.

Added in Nilearn 0.5.1.

This function returns a Deterministic atlas, and the provided images are in MNI152 space.

For more information on this dataset, see Schaefer 2018 parcellation[1], Schaefer et al.[2], and Thomas Yeo et al.[3].

Parameters:
n_rois{100, 200, 300, 400, 500, 600, 700, 800, 900, 1000}, default=400

Number of regions of interest.

yeo_networks{7, 17}, default=7

ROI annotation according to yeo networks.

resolution_mm{1, 2}, default=1mm

Spatial resolution of atlas image in mm.

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.

base_urlstr, default=None

Base URL of files to download (None results in default base_url).

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:

  • ‘maps’: str, path to nifti file containing the

    3D Nifti1Image (its shape is (182, 218, 182)). The values are consecutive integers between 0 and n_rois which can be interpreted as indices in the list of labels.

  • ‘labels’list of str

    List of the names of the regions.

  • ‘description’str

    Description of the dataset.

  • lutpandas.DataFrame

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

  • ‘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.

  • ‘atlas_type’str

    Type of atlas. See Probabilistic atlas and Deterministic atlas.

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.

Release v0.14.3 of the Schaefer 2018 parcellation is used by default. Versions prior to v0.14.3 are known to contain erroneous region label names. For more details, see https://github.com/ThomasYeoLab/CBIG/blob/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal/Parcellations/Updates/Update_20190916_README.md

License: MIT.

References