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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.
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
[get_dataset_dir] Dataset created in /home/runner/nilearn_data/Megatrawls
[fetch_single_file] Downloading data from
http://www.nitrc.org/frs/download.php/8037/Megatrawls.tgz ...
[fetch_single_file] ...done. (1 seconds, 0 min)
[uncompress_file] Extracting data from
/home/runner/nilearn_data/Megatrawls/3f1468dc43a408bf84510b07cee95049/Megatrawls
.tgz...
[uncompress_file] .. done.
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()
Total running time of the script: (0 minutes 1.766 seconds)
Estimated memory usage: 147 MB
