Closed emdupre closed 5 years ago
Based on poldracklab/fmriprep#1010, it seems like fMRIPrep will ultimately incorporate the full tedana pipeline. However, at the moment, I think the most appropriate approach is to take the fully preprocessed time series (func/*bold_space-<space>_preproc.nii.gz
), and optionally also the brain mask (func/*bold_space-<space>_brainmask.nii.gz
), from fMRIPrep to use in tedana.
One fMRIPrep setting to use is --t2s-coreg
, and one to not use is probably --use-aroma
. It's also probably not a good idea to output surfaces if we end up dropping surface support in tedana. It doesn't seem like there are any flags in tedana that should or shouldn't be used when processing fMRIPrep derivatives, except possibly --mask
.
@emdupre Is that the kind of information you were thinking of?
This is good info (I asked this question on here recently! :) )
As a suggestion it could be great to show some results within the documentation with open source data for example using: https://openneuro.org/datasets/ds000258/versions/00002
I believe that that's something we're (slowly) working toward in the tedana-comparison repository. The main goal there is to compare different versions of tedana across a number of public datasets, but it will include visual reports that we'll be able to feed into the documentation for tedana proper.
awesome!
Since both fmriprep and afni_proc.py will (soon -- see https://github.com/poldracklab/fmriprep/pull/1296) call tedana directly, it might also make sense to have documentation on what a pipeline including tedana minimally requires, in case users / developers want to build their own.
We should have documentation on how to interact with other pipelines like AFNI and fMRIPrep !