AFNI version info (afni -ver):
Precompiled binary linux_ubuntu_16_64: Apr 5 2024 (Version AFNI_24.1.01 'Publius Septimius Geta')
Is there any way to filter out cardiac, and respiratory nuisances without warping? How about at least without oblique warping or changing the plane? If so, how would I do this?
If you are using afni_proc.py, you can leave out the "align" and "tlrc" blocks, so that the EPI dataset stays in its own space. Note that motion correction inherently blurs the data a little bit, regridding volumes even if it is to their own grid.
If you have physio and cardiac time series, you could use physio_calc.py to make those into regressors that are included with the "ricor" block (-> performing RETROICOR).
An example with retroicor is provided in the afni_proc.py paper, Ex. 3:
Reynolds RC, Glen DR, Chen G, Saad ZS, Cox RW, Taylor PA (2024). Processing, evaluating and understanding FMRI data with afni_proc.py.here.
... and the physio_calc.py description posters are:
Lauren PD, Glen DR, Reynolds RC, Taylor PA (2023). physio_calc.py: New program to model cardiac & respiratory contributions to BOLD signal in AFNI. Presented at the 29th Annual Meeting of the Organization for Human Brain Mapping. https://afni.nimh.nih.gov/pub/dist/OHBM2023/ohbm_2023_PeterLauren.pdf
The
National Institute of Mental Health (NIMH) is part of the National Institutes of
Health (NIH), a component of the U.S. Department of Health and Human
Services.