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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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Thank you Rick. That makes sense.
What would be considered a reasonably good SNR?
Regards,
George
by
gchahine
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AFNI Message Board
Dear all,
I have a question regarding the TSNR image outputted from the afni_proc.py program. The explanation provided is the following:
By default, a temporal signal to noise (TSNR) dataset is created at
the end of the regress block. The "signal" is the all_runs dataset
(input to 3dDeconvolve), and the "noise" is the errts dataset (the
by
gchahine
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AFNI Message Board
The issue is that the aim is to do seed-based analysis, and afaik bandpass filtering is a requirement. What I was suggesting is to include a regressor in the regression analysis for the volumes to be censored without actually removing the timepoints during regression. I do not know however if bandpass filtering in that case would still be valid.
Thank you for your help,
George
by
gchahine
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AFNI Message Board
Hi Rick,
These are the instances when the warning message is coming:
set minindex = `3dTstat -argmin -prefix - outcount_rall.1D\'`
3dTstat -argmin -prefix - outcount_rall.1D'
++ 3dTstat: AFNI version=AFNI_17.2.02 (Jul 10 2017) [64-bit]
++ Authored by: KR Hammett & RW Cox
*+ WARNING: Input dataset is not 3D+time; assuming TR=1.0
set ovals = ( `1d_tool.py -set_run_lengths $
by
gchahine
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AFNI Message Board
Hi Rick,
Just to follow up on this, I'm noticing that when I run the afni_proc.py script I am getting the following warning:
"*+ WARNING: Input dataset is not 3D+time; assuming TR=1.0"
after 3dTstat is called. I am wondering if this has any influence on how the bandpass filtering later, as the TR is 2 seconds.
Thank you,
George
by
gchahine
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AFNI Message Board
Thank you.
I was additionally thinking of rather than actually deleting the volumes, I could put in a regressor file with a dummy variable (0 for volumes above threshold and 1 for those that are not) in the regression model. The volumes could be deleted then after temporal regression if needed.
I am wondering what do people think about this approach. Really appreciate the help.
by
gchahine
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AFNI Message Board
Thank you Rick.
I am starting out with 147 volumes and TR is 2s. The error message points out that there are 108 parameters to estimate.
What is a possible way around this? I know it's not optimal, but it seems most studies censor before applying a regression model that includes both a temporal filter and nuisance variables. Would that make a difference?
An other possible option is
by
gchahine
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AFNI Message Board
Dear all,
I am running afni_proc.py on resting state data and in my regression model I'm specifying motion censoring (i.e "scrubbing" for enorm values exceeding 0.3 mm) and temporal filtering (0.01-0.1 Hz). Unfortunately 3dDeconvolve is failing to run for many of the subjects in my study. I'm aware that this is a consequence of censoring as it decreases the amount of data a
by
gchahine
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AFNI Message Board
I am just going through more data now and even though what I mentioned before corrected many of the issues: one issue with some subjects is that EPI data does not seem very well skullstripped which is throwing off the alignment with the anatomical (skull of EPI data on brain of anatomical). Any way to address this issue?
Thanks a lot,
George
by
gchahine
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AFNI Message Board
Thank you pt and RWCox.
I "deobliqued" my EPI and then used @Align_Centers to center the EPI and the skull stripped anatomical at the center of mass before running afni_proc.py and this seems to have solved the issue. I don't think I need -giant_move or use another cost function just yet.
Are there any concerns for aligning the EPI and the anatomical before running the other pr
by
gchahine
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AFNI Message Board
Thank you pt. I am using afni_proc.py to preprocess resting state images. I am essentially registering the anatomical to the EPI and using non-linear warping for standardization. Some of the images turn out fine but quite a few of them are far off. I was looking for something similar to SPM's function to reset the origin or tilt/rotate the image; this essentially just changes the origin with
by
gchahine
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AFNI Message Board
Dear all,
I am preprocessing a large batch of subjects and with some subjects the registration is significantly off. I am looking into manually reorienting the images (setting origin, possible rotating..etc) in a similar way that can be done in SPM. I am not sure if this option is available in AFNI. I tried to do it in SPM and have AFNI read the image but it doesn't seem it is reading the
by
gchahine
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AFNI Message Board
Hi everyone,
I am running a resting state analysis with afni_proc.py . I would like to do one analysis without global signal regression and another analysis with global signal regression. Is there any way to make this work without having to repeat all the steps twice? Can I specify that in the command option that generates the script file?
Thanks a lot in advance,
George
by
gchahine
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AFNI Message Board
Hi everyone,
I am preprocessing some resting state date with afni_proc.py. I understand the errts image is basically the image file after the regression analysis. What's putting me off a little is that there are non-zero voxel values outside the brain mask. All of the other prior outputs seem fine. I am not sure if this is standard (need to apply a mask later to limit non-zero voxel areas
by
gchahine
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AFNI Message Board