AFNI Message Board

Dear AFNI users-

We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:

https://discuss.afni.nimh.nih.gov

Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.

The current Message Board discussion threads have been migrated to the new framework. The current Message Board will remain visible, but read-only, for a little while.

Sincerely, AFNI HQ

History of AFNI updates  

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March 08, 2022 11:34AM
Iliara,
I would not consider myself an AFNI expert, but I would not recommend "mixing and matching" these preprocessing pipelines, as neither of them are designed to interoperate. fMRIPrep is intended to replace all other programs' preprocessing, by doing the "mixing and matching" between major packages for you. If your plan is to do a GLM, etc. in AFNI then I would recommend just using afni_proc.py. There are many subtle sorts of errors (see below) that can be introduced if you're not very careful.

1. Yes, the order is relevant. See the 3dvolreg help under "-dfile": [afni.nimh.nih.gov]
> n roll pitch yaw dS dL dP rmsold rmsnew
2. Yes, any ASCII text matching AFNI's specifications for a regressor should work; see, for example, the help for 3dREMLfit: [afni.nimh.nih.gov] (unless you mean to censor motion, in which case it's probably easier to manually specify volumes that you would like censored in 3dDeconvolve; see -CENSORTR)
3. Sorry, I'll have to wait for somebody else to answer that.
4. Additional regressors will not impact motion censoring.

For slice timing, the note in 3dTshift points out how the timings affect operations like 3dDeconvolve: [afni.nimh.nih.gov]
> The new slice/volume timing is intended to be the real timing from the
start of the run.

> How might this affect stimulus timing in 3dDeconvolve?
3dDeconvolve creates regressors based on volume times of k*TR, matching
tzero=0. So an event at run time t=0 would start at the time of volume
#0. However using -tzero 1 (or the default, in the case of TR~=2s),
an event at run time t=0 would then be 1s *before* the first volume.
Note that this matches reality. An event at time t=0 happens before
all but the first acquired slice. In particular, a slice acquired at
TR offset 1s might be unaffected by 3dTshift. And an event at run time
t=0 seems to happen at time t=-1s from the perspective of that slice.

> To align stimulus times with the applied tzero of 3dTshift, tzero
should be subtracted from each stimulus event time (3dDeconvolve
effectively subtracts tzero from the EPI timing, so that should be
applied to the event times as well).

It is not clear to me if fMRIPrep would make the same guarantees as 3dTshift (representing a possible interoperability issue).

However, 1s is pretty short, you may use slice time correction but it may not make much of a difference.
Subject Author Posted

AFNIproc.py after fMRIprep.

Ilaria March 07, 2022 06:07PM

Re: AFNIproc.py after fMRIprep.

jbteves March 08, 2022 11:34AM

Re: AFNIproc.py after fMRIprep.

jbteves March 08, 2022 11:37AM

Re: AFNIproc.py after fMRIprep.

rick reynolds March 08, 2022 01:15PM

Re: AFNIproc.py after fMRIprep.

Ilaria March 08, 2022 01:35PM

Re: AFNIproc.py after fMRIprep.

audachang December 03, 2022 03:26AM

Re: AFNIproc.py after fMRIprep.

rick reynolds December 04, 2022 11:39PM