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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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Results 1 - 30 of 39
Thanks, I think I have tried most of the options in the help text.
The skullstrip is good, but the functional data has rather low contrast (I downloaded it so cannot change scanner parameters).
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kickan
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AFNI Message Board
Is it possible to do rigid registration between epi and anatomical in afni_proc.py? I have tried many options and the registration always makes the EPI volume too big, therefore I would like to try a rigid 6 parameter registration instead of an affine 12 parameter registration.
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kickan
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AFNI Message Board
I just installed AFNI on a Macbook, El Capitan, and if I run functions as sudo, e.g. "sudo 3dinfo" it works, but if I run the same function without the sudo it complains about a missing iconv library. Any ideas?
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kickan
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AFNI Message Board
Thanks for your replies.
Do you know if anyone has tried non-linear registration, instead of affine registration? I know that non-linear registration is much more time consuming, but it would be interesting to compare it to affine registration.
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kickan
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AFNI Message Board
I only have data from the human connectome project, I usually don't collect data myself. Right now I'm only interested in the motion correction, not the eddy current correction, as I just recently started with DTI (worked with fMRI for a long time).
I have a pretty good registration algorithm, and I want to test how it performs compared to other algorithms for DTI. For DTI data, ther
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kickan
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AFNI Message Board
Thanks
Are you aware of any comparison between motion correction tools for DTI?
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kickan
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AFNI Message Board
Is there a specific AFNI tool for motion correction of DTI data? I know about 3dvolreg for fMRI, but can it also be used for DTI?
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kickan
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AFNI Message Board
If there are several runs in an fMRI dataset, AFNI seems to add a different set of detrending regressors for each run, but there is only one set of activity regressors and one set of motion regressors. SPM, on the other hand, seems to add one set of activity regressors and one set of motion regressors per run.
I'm not saying that either way is wrong, but it would be interesting to know wh
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kickan
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AFNI Message Board
In SPM and FSL it is possible to get p-values for each voxel, corrected for multiple comparisons using the familywise error rate (based on Gaussian random field theory). In AFNI I think it is only possible to get this for clusters, using 3dClustSim. Is it somehow possible to get corrected p-values for each voxel in AFNI?
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kickan
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AFNI Message Board
Is it possible to get voxel based p-values with familywise error rate correction in AFNI? I know about FDR and your cluster FWE, but I would like to compare voxel FWE to SPM and FSL.
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kickan
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AFNI Message Board
I would like to apply the "clusterize" button that is available in the AFNI gui, as a command. I would then like AFNI to jump to the biggest cluster, is that possible?
I would like to do something like
afni -com 'OPEN_WINDOW A.axialimage' \
-com 'SWITCH_UNDERLAY data+tlrc.HEAD' \
-com 'SWITCH_OVERLAY data+tlrc.HEAD' \
-c
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kickan
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AFNI Message Board
I set ndim to 3, dim[5] is 1
I'm not sure where the '160' comes from
header file 'bold_pvalues_contrast1_EPI.nii.gz', num_fields = 43
all fields:
name offset nvals values
------------------- ------ ----- ------
sizeof_hdr 0 1 348
data_type 4 10
db_name 14 18
exte
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kickan
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AFNI Message Board
I have created a nifti file in my own fMRI program. If I look at it with 3dinfo it says that there are 160 volumes. If I look at it with fslinfo it says that there is only one volume. How do I change the nifti header such that AFNI understands that there is only one volume?
This is what I have changed so far
nifti_image *outputNiftiStatisticsEPI = nifti_copy_nim_info(inputfMRI);
outputNift
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kickan
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AFNI Message Board
I just noticed that you have made some changes to the 3dClustSim function. I appreciate that you improve the functionality in AFNI, and have some feature requests.
It would be nice if you can select the distance type (NN1, NN2, NN3), if you are only interested in one of them.
It would be nice if you can select the thresholding type (one-sided, two-sided, bi-sided), if you are only intereste
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kickan
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AFNI Message Board
There seems to be different ways to create a group mask, one can use 3dMean with -mask_inter, but what should the individual masks be? Some seem to use mask_group+tlrc.HEAD, but that mask seems very general and does not seem to fit the data in all cases. Is it better to use full_mask.sub+tlrc.HEAD?
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kickan
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AFNI Message Board
Great, thanks. This part of the help text for 3dDeconvolve made me a bit confused, and was the reason I proposed IM instead of AM.
*N.B.: You can also use dmBLOCK with -stim_times_IM, in which case
each time in the 'tname' file should have just ONE extra
parameter -- the duration -- married to it, as in '30:15',
meaning a block of
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kickan
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AFNI Message Board
I only want one beta per voxel, so this should be OK?
-regress_stim_types AM1
-regress_stim_times events.txt
-regress_stim_labels events
-regress_basis 'dmBLOCK'
-regress_opts_3dD
-stim_times_AM1
-gltsym 'SYM: events' -glt_label 1 activity
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kickan
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AFNI Message Board
R-to-L extent: -79.500 -to- 79.500 -step- 3.000 mm [ 54 voxels]
A-to-P extent: -79.500 -to- 109.500 -step- 3.000 mm [ 64 voxels]
I-to-S extent: -63.500 -to- 83.500 -step- 3.000 mm [ 50 voxels]
Not sure what you mean by bounding box, but the mask used is the regular full_mask
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kickan
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AFNI Message Board
I would like to analyze event related fMRI data, where the duration of each event differs. I have tried to read the help texts of afni_proc.py and 3dDeconvolve. My current solution looks like this, is it OK?
Part of call to afni_proc.py
-regress_stim_types IM
-regress_stim_times events.txt
-regress_stim_labels events
-regress_basis 'dmBLOCK'
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kickan
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AFNI Message Board
I used afni_proc.py to analyze some fMRI data and applied different levels of smoothing. I then looked at the smoothness estimates and got a bit confused, why does the smoothness estimation not work for high degrees of smoothing?
Applied smoothing
4 mm
6 mm
8 mm
10 mm
12 mm
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kickan
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AFNI Message Board
Thanks.
How does 3drefit work if I change from LPI to RPI? Does it actually rearrange the data, or is only the header changed?
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kickan
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AFNI Message Board
If I do "3dinfo" on a nifti file I can see the orientation (e.g. LPI, RPI). When I look at the nifti documentation, I cannot see a field that provides this information (http://brainder.org/2012/09/23/the-nifti-file-format/). How does AFNI get the orientation from the nifti header?
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kickan
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AFNI Message Board
I don't use any covariates, I'm just doing a simple two-sample t-test.
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kickan
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AFNI Message Board
Precompiled binary linux_openmp_64: Aug 13 2014 (Version AFNI_2011_12_21_1014)
3dMEMA -groups A B -mask group_mask.nii -prefix results_MEMA -jobs 8 \
-set A \
${Subject1} "$GroupDirectory/${Subject1}.results/stats.${Subject1}_REML+tlrc[1]" "$GroupDirectory/${Subject1}.results/stats.${Subject1}_RE
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kickan
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AFNI Message Board
I'm trying to use 3dMEMA for group analysis. Without a mask it works fine, but when I add '-mask group_mask.nii' (which works with 3dttest++) I get the following error
Error in if (is.na(size)) { : argument is of length zero
Calls: process.MEMA.opts -> read.AFNI
In addition: Warning messages:
1: In readLines(conhead) : line 1 appears to contain an embedded nul
2: In readL
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kickan
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AFNI Message Board
But doesn't it make more sense to estimate the smoothness from the residuals of the group analysis? That's how the smoothness is estimated from each subject.
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kickan
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AFNI Message Board
I used 3dClustSim to calculate familywise corrected p-values for clusters, and according to the help text the function by default uses one sided uncorrected voxel-wise p-values to define the clusters. So far so good. However, when I open the AFNI GUI and set the threshold slider to p = 0.01 (which I also used as a voxel-wise threshold for 3dClustSim), the corresponding test value is about 2.70. A
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kickan
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AFNI Message Board
Is there a recommended cluster defining threshold to use? Is p = 0.01 standard?
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kickan
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AFNI Message Board
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