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_oasis_vbm¶
- nilearn.datasets.fetch_oasis_vbm(n_subjects=None, dartel_version=True, data_dir=None, url=None, resume=True, verbose=1)[source]¶
Download and load Oasis “cross-sectional MRI” dataset (416 subjects).
Data Usage Agreement
Using data available through the OASIS project requires agreeing with the Data Usage Agreement that can be found at https://sites.wustl.edu/oasisbrains/
- Parameters:
- n_subjects
int, default=None The number of subjects to load. If None is given, all the subjects are used.
- dartel_version
bool, default=True Whether or not to use data normalized with DARTEL instead of standard SPM8 normalization.
- data_dir
pathlib.Pathorstror None, optional Path where data should be downloaded. By default, files are downloaded in a
nilearn_datafolder in the home directory of the user. See alsonilearn.datasets.utils.get_data_dirs.- url
stror None, 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
boolorint, default=1 Verbosity level (
0orFalsemeans no message).
- n_subjects
- Returns:
- dataBunch
Dictionary-like object, the interest attributes are :
‘gray_matter_maps’: string list Paths to nifti gray matter density probability maps
‘white_matter_maps’ string list Paths to nifti white matter density probability maps
‘ext_vars’: pandas.DataFrame Data from the .csv file with information about selected subjects
‘data_usage_agreement’: string Path to the .txt file containing the data usage agreement.
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.
For more information see the dataset description.
Examples using nilearn.datasets.fetch_oasis_vbm¶
Voxel-Based Morphometry on Oasis dataset with Space-Net prior