9.2.4. Visualizing Megatrawls Network Matrices from Human Connectome Project

This example shows how to fetch network matrices data from HCP beta-release of the Functional Connectivity Megatrawl project.

See nilearn.datasets.fetch_megatrawls_netmats documentation for more details.

9.2.4.1. Fetching the Megatrawls Network matrices

Fetching the partial correlation matrices of dimensionality d=300 with timeseries method ‘eigen regression’

from nilearn import datasets

netmats = datasets.fetch_megatrawls_netmats(dimensionality=300,
                                            timeseries='eigen_regression',
                                            matrices='partial_correlation')
# Partial correlation matrices array of size (300, 300) are stored in the name
# of 'correlation_matrices'
partial_correlation = netmats.correlation_matrices

Out:

Dataset created in /home/varoquau/nilearn_data/Megatrawls

Downloading data from http://www.nitrc.org/frs/download.php/8037/Megatrawls.tgz ...

Downloaded 114688 of 3066300 bytes (3.7%,   31.3s remaining)
Downloaded 344064 of 3066300 bytes (11.2%,   19.3s remaining)
Downloaded 737280 of 3066300 bytes (24.0%,   11.6s remaining)
Downloaded 1302528 of 3066300 bytes (42.5%,    6.6s remaining)
Downloaded 2048000 of 3066300 bytes (66.8%,    3.0s remaining)
Downloaded 2973696 of 3066300 bytes (97.0%,    0.2s remaining) ...done. (11 seconds, 0 min)
Extracting data from /home/varoquau/nilearn_data/Megatrawls/68c41934c6cf43be91dd107f913ffd01/Megatrawls.tgz..... done.

9.2.4.2. Visualization

Import nilearn plotting modules to use its utilities for plotting correlation matrices

from nilearn import plotting

title = "Partial correlation matrices\n for d=300"
display = plotting.plot_matrix(partial_correlation, colorbar=True,
                               title=title)
plotting.show()