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).
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
, optional If True, returns an atlas with distinct regions for right and left hemispheres. Default=True.
- data_dir
pathlib.Path
orstr
, optional Path where data should be downloaded. By default, files are downloaded in home directory.
- url
str
, optional URL of file to download. Override download URL. Used for test only (or if you setup a mirror of the data). Default=None.
- resume
bool
, optional Whether to resume download of a partly-downloaded file. Default=True.
- verbose
int
, optional Verbosity level (0 means no message). Default=1.
- legacy_format
bool
, optional If set to
True
, the fetcher will return recarrays. Otherwise, it will return pandas dataframes. Default=True.
- 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
- 1
Bruce Fischl, André van der Kouwe, Christophe Destrieux, Eric Halgren, Florent Ségonne, David H. Salat, Evelina Busa, Larry J. Seidman, Jill Goldstein, David Kennedy, Verne Caviness, Nikos Makris, Bruce Rosen, and Anders M. Dale. Automatically Parcellating the Human Cerebral Cortex. Cerebral Cortex, 14(1):11–22, 01 2004. URL: https://doi.org/10.1093/cercor/bhg087, arXiv:https://academic.oup.com/cercor/article-pdf/14/1/11/1193353/bhg087.pdf, doi:10.1093/cercor/bhg087.
- 2
C Destrieux, B Fischl, AM Dale, and E Halgren. A sulcal depth-based anatomical parcellation of the cerebral cortex. NeuroImage, 47(Supplement 1):S151, 2009. doi:10.1016/S1053-8119(09)71561-7.
Examples using nilearn.datasets.fetch_atlas_destrieux_2009
#
Making a surface plot of a 3D statistical map