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_msdl#

nilearn.datasets.fetch_atlas_msdl(data_dir=None, url=None, resume=True, verbose=1)[source]#

Download and load the MSDL brain Probabilistic atlas.

It can be downloaded at [1], and cited using [2]. See also [3] for more information.

Parameters:
data_dirpathlib.Path or str, optional

Path where data should be downloaded. By default, files are downloaded in home directory.

urlstr, optional

URL of file to download. Override download URL. Used for test only (or if you setup a mirror of the data). Default=None.

resumebool, optional

Whether to resume download of a partly-downloaded file. Default=True.

verboseint, optional

Verbosity level (0 means no message). Default=1.

Returns:
datasklearn.utils.Bunch

Dictionary-like object, the interest attributes are :

  • ‘maps’: str, path to nifti file containing the Probabilistic atlas image (shape is equal to (40, 48, 35, 39)).

  • ‘labels’: list of str, list containing the labels of the regions. There are 39 labels such that data.labels[i] corresponds to map i.

  • ‘region_coords’: list of length-3 tuple, data.region_coords[i] contains the coordinates (x, y, z) of region i in MNI space.

  • ‘networks’: list of str, list containing the names of the networks. There are 39 network names such that data.networks[i] is the network name of region i.

  • ‘description’: str, description of the atlas.

References

Examples using nilearn.datasets.fetch_atlas_msdl#

Visualizing a probabilistic atlas: the default mode in the MSDL atlas

Visualizing a probabilistic atlas: the default mode in the MSDL atlas

Visualizing a probabilistic atlas: the default mode in the MSDL atlas
Visualizing 4D probabilistic atlas maps

Visualizing 4D probabilistic atlas maps

Visualizing 4D probabilistic atlas maps
Extracting signals of a probabilistic atlas of functional regions

Extracting signals of a probabilistic atlas of functional regions

Extracting signals of a probabilistic atlas of functional regions
Computing a connectome with sparse inverse covariance

Computing a connectome with sparse inverse covariance

Computing a connectome with sparse inverse covariance
Group Sparse inverse covariance for multi-subject connectome

Group Sparse inverse covariance for multi-subject connectome

Group Sparse inverse covariance for multi-subject connectome
Classification of age groups using functional connectivity

Classification of age groups using functional connectivity

Classification of age groups using functional connectivity
Functional connectivity predicts age group

Functional connectivity predicts age group

Functional connectivity predicts age group