To be precise, high_variance_confounds() is applied in this example to the whole image, including the space around the brain, which is probably not the case for the compcorr provided with the adhd dataset.

I removed the call to high_variance_confounds() from **plot_region_covariance.py**. I tested that the result is almost unchanged. However, if I do the same in **plot_msdl_covariance_advanced.py**, the graph lasso does not converge, even if the result is really close to what it was before. We're not using the same regions (MSDL / Harvard-Oxford.)