Why is there GLM for resting state data?

Hi there, im recently learning Nilearn using preprocessed rest-fMRI data (fMRIprep).

From what i understand, GLM is to fit a theretical model to realistic BOLD signals according to stimulus onset.

Thats why im a bit confused by this page :
Default Mode Network extraction of ADHD dataset - Nilearn

If there is no stimulus at all (rest data), why do we need to do the GLM?

And they calculated frametimes and chose a HRF for GLM analysis, why is there HRF at all if the data is at rest…

im totally lost and any help would be greatly appreciated!!!

Big picture explanation:

So this example, extract the activity from a region (the seed) and uses the time course from that region as regressor in a GLM: this will show you which regions have an activity that is correlated with seed region.

Does that help?

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quite straightforward explanation and much more explicit than the tutorials (or it was me who was skipping lines)