.. _example_connectivity_plot_probabilistic_atlas_extraction.py:


Extracting signals of a probabilistic atlas of rest functional regions
========================================================================

This example extracts the signal on regions defined via a probabilistic
atlas, to construct a functional connectome.

We use the `MSDL atlas
<https://team.inria.fr/parietal/research/spatial_patterns/spatial-patterns-in-resting-state/>`_
of functional regions in rest.

The key to extract signals is to use the
:class:`nilearn.input_data.NiftiMapsMasker` that can transform nifti
objects to time series using a probabilistic atlas.

As the MSDL atlas comes with (x, y, z) MNI coordinates for the different
regions, we can visualize the matrix as a graph of interaction in a
brain. To avoid having too dense a graph, we represent only the 20% edges
with the highest values.




.. rst-class:: sphx-glr-horizontal





**Python source code:** :download:`plot_probabilistic_atlas_extraction.py <plot_probabilistic_atlas_extraction.py>`

.. literalinclude:: plot_probabilistic_atlas_extraction.py
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**Total running time of the example:**  0.00 seconds
( 0 minutes  0.00 seconds)