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_surf_nki_enhanced

nilearn.datasets.fetch_surf_nki_enhanced(n_subjects=10, data_dir=None, url=None, resume=True, verbose=1)[source]

Download and load the NKI enhanced resting-state dataset, preprocessed and projected to the fsaverage5 space surface.

Added in Nilearn 0.3.

Parameters:
n_subjectsint, default=10

The number of subjects to load from maximum of 102 subjects. By default, 10 subjects will be loaded. If None is given, all 102 subjects will be loaded.

data_dirpathlib.Path or str or None, 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 also nilearn.datasets.utils.get_data_dirs.

urlstr or None, default=None

URL of file to download. Override download URL. Used for test only (or if you setup a mirror of the data).

resumebool, default=True

Whether to resume download of a partly-downloaded file.

verbosebool or int, default=1

Verbosity level (0 or False means no message).

Returns:
datasklearn.utils.Bunch

Dictionary-like object, the interest attributes are :

  • ‘func_left’: Paths to Gifti files containing resting state

    time series left hemisphere

  • ‘func_right’: Paths to Gifti files containing resting state

    time series right hemisphere

  • ‘phenotypic’: pd.DataFrame containing tuple with subject ID, age,

    dominant hand and sex for each subject.

  • ‘description’: data description of the release and references.

scipy >= 0.14.0 compatibility

It may be necessary to coerce to float the data loaded from the Gifti files to avoid issues with scipy >= 0.14.0.

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.