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 Fischl et al.[1], and Destrieux et al.[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:
- lateralized
bool
, default=True If True, returns an atlas with distinct regions for right and left hemispheres.
- data_dir
pathlib.Path
orstr
, 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 alsonilearn.datasets.utils.get_data_dirs
.- url
str
, default=None URL of file to download. Override download URL. Used for test only (or if you setup a mirror of the data).
- resume
bool
, default=True Whether to resume download of a partly-downloaded file.
- verbose
int
, default=1 Verbosity level (0 means no message).
- legacy_format
bool
, default=True If set to True, the fetcher will return recarrays. Otherwise, it will return pandas dataframes.
- lateralized
- Returns:
- data
sklearn.utils.Bunch
Dictionary-like object, contains:
‘maps’:
str
, path to nifti file containing theNifti1Image
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. Iflegacy_format
is set toFalse
, this is apandas.DataFrame
.‘description’:
str
, description of the atlas.
- data
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