"minimum image regression" in tedana

I have cardiac-gated, multi-echo data. I want to use tedana to combine the echoes, remove T1-related noise, and NOTHING else.
My question is: Can I simply use the option --gscontrol mir? Or do I need to go inside tedana code and modify something?

On the tedana website, it says
MIR (minimum image regression): Perform minimum image regression (MIR) to remove T1-like effects from BOLD-like components.

Thank you so much

There is no option to just run MIR. From what I can recall of the MIR method, as implemented in tedana, it requires the ICA and component classification steps to work. However, what you can do is run tedana with MIR enabled, and then regress the T1-related noise map from the optimally combined data, without using the denoising derivatives. Does that sound reasonable?

Thank you Tsalo.
I don’t know to regress T1-related noise from tedana output. I don’t think you mean to look at the timeseries of each rejected component and decide which one is T1-related, correct?

When I use the option --gscontrol mir, I got outputs including
desc-optcomMIRDenoised_bold.nii.gz, and

desc-T1likeEffect_min…nii.gz is 3D. The old manual only says it contains T1-like effect. Could you please let me what this file represent?

I believe we should use desc-optcomDenoised_bold.nii.gz for further processing. In this case, what is the difference between desc-optcomDenoised_bold.nii.gz and desc-optcomMIRDenoised_bold.nii.gz?

Does desc-optcomMIRDenoised_bold.nii.gz have T1-related noise AND other noisy ICA components removed?