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_destrieux_2009#

nilearn.datasets.fetch_atlas_destrieux_2009(lateralized=True, data_dir=None, url=None, resume=True, verbose=1, legacy_format=True)[source]#

Download and load the Destrieux cortical deterministic atlas (dated 2009).

See [1], and [2].

Note

Some labels from the list of labels might not be present in the atlas image, in which case the integer values in the image might not be consecutive.

Parameters:
lateralizedbool, optional

If True, returns an atlas with distinct regions for right and left hemispheres. Default=True.

data_dirpathlib.Path or str, optional

Path where data should be downloaded. By default, files are downloaded in home directory.

urlstr, optional

URL of file to download. Override download URL. Used for test only (or if you setup a mirror of the data). Default=None.

resumebool, optional

Whether to resume download of a partly-downloaded file. Default=True.

verboseint, optional

Verbosity level (0 means no message). Default=1.

legacy_formatbool, optional

If set to True, the fetcher will return recarrays. Otherwise, it will return pandas dataframes. Default=True.

Returns:
datasklearn.utils.Bunch

Dictionary-like object, contains:

  • ‘maps’: str, path to nifti file containing the Nifti1Image defining the cortical ROIs, lateralized or not. The image has shape (76, 93, 76), and contains integer values which can be interpreted as the indices in the list of labels.

  • ‘labels’: numpy.recarray, rec array containing the names of the ROIs. If legacy_format is set to False, this is a pandas.DataFrame.

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

References

Examples using nilearn.datasets.fetch_atlas_destrieux_2009#

Making a surface plot of a 3D statistical map

Making a surface plot of a 3D statistical map

Making a surface plot of a 3D statistical map