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.

fetch_atlas_basc_multiscale_2015

nilearn.datasets.fetch_atlas_basc_multiscale_2015(data_dir=None, url=None, resume=True, verbose=1, resolution=7, version='sym')[source]

Download and load multiscale functional brain parcellations.

This Deterministic atlas includes group brain parcellations generated from resting-state functional magnetic resonance images from about 200 young healthy subjects.

For more information see the dataset description.

Added in Nilearn 0.2.3.

Parameters:
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).

resolutionint, default=7

Number of networks in the dictionary. Valid resolutions available are {7, 12, 20, 36, 64, 122, 197, 325, 444}

version{‘sym’, ‘asym’}, default=’sym’

Available versions are ‘sym’ or ‘asym’. By default all scales of brain parcellations of version ‘sym’ will be returned.

Returns:
datasklearn.utils.Bunch

Dictionary-like object, contains:

  • maps: str

    Path to Nifti file of the brain parcellation. Images have shape (53, 64, 52) and contain consecutive integer values from 0 to the selected number of networks (scale).

  • ‘description’str

    Description of the dataset.

  • lut : pandas.DataFrame

    Act as a look up table (lut) with at least columns ‘index’ and ‘name’. Formatted according to ‘dseg.tsv’ format from BIDS.

  • ‘template’str

    The standardized space of analysis in which the data is provided. When known it should be a valid template name taken from the spaces described in the BIDS specification.

  • ‘atlas_type’ : str

    Type of atlas. See Probabilistic atlas and Deterministic atlas.

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.

Examples using nilearn.datasets.fetch_atlas_basc_multiscale_2015

Visualizing multiscale functional brain parcellations

Visualizing multiscale functional brain parcellations

Working with long time series fMRI images

Working with long time series fMRI images