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_coords_dosenbach_2010(ordered_regions=True, legacy_format=True)[source]#

Load the Dosenbach et al 160 ROIs.

These ROIs cover much of the cerebral cortex and cerebellum and are assigned to 6 networks.

See Dosenbach et al.[1].

ordered_regionsbool, default=True

ROIs from same networks are grouped together and ordered with respect to their names and their locations (anterior to posterior).

legacy_formatbool, default=True

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


Dictionary-like object, contains:

  • ‘rois’: numpy.recarray, rec array with the coordinates of the 160 ROIs in MNI space. If legacy_format is set to False, this is a pandas.DataFrame.

  • ‘labels’: numpy.ndarray of str, list of label names for the 160 ROIs.

  • ‘networks’: numpy.ndarray of str, list of network names for the 160 ROI.

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


Examples using nilearn.datasets.fetch_coords_dosenbach_2010#

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