Minimum image regression relies on distinction between "accepted" and "ignored" components

ME-ICA / tedana

TE-dependent analysis of multi-echo fMRI

https://tedana.readthedocs.io

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Minimum image regression relies on distinction between "accepted" and "ignored" components #1085

Open tsalo opened 2 months ago

tsalo commented 2 months ago

Summary

I'm working on refactoring the global signal regression functions in order to better understand them (particularly for #1071), and I noticed that gscontrol.minimum_image_regression specifically uses "accepted" components and not "ignored" components. Since we eliminated the "ignored" classification in #756, MIR likely doesn't work the way it was intended anymore.

We could probably leverage the classification tags, but those vary by decision tree and are essentially up to the user.

tsalo commented 2 months ago

Ah, I see that "low variance" and "accept borderline" only exist as classification tags in the meica and tedana_orig trees.