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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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Hi Rick,
thanks for the feedback.
This is a resting-state run, hence processed with a resting-state script. I compute the autocorrelation across the complete run. I applied cubic polynomial interpolation on the .errts file in Python, and the before (.errts without interpolation) vs. after (.errts with interpolation) look good when I plot the time-series.
One question: is there a chance tha
by
Philipp
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AFNI Message Board
I am interested in computing the signal’s autocorrelation.
Some subjects showed heavy head motion now and then. Therefore, and in order to keep the time-series intact, I wanted to rather censore (and then interpolate) the respective TRs.
However, I now think that I will run the interpolation in Python, such as via cubic splines.
Let me know if you have any comments on this from the AFNI si
by
Philipp
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AFNI Message Board
Hi,
I have a methodological or computational question regarding the "-cenmode NTRP" function by 3dTproject that uses linear interpolation on censored sampling points.
This option is not yet implemented in AFNI proc.
Would it be ok to run AFNI proc with motion censoring, and, after AFNI proc finished, to go back to the "pb04...r01.blur+tlrc.HEAD" file in order to run -c
by
Philipp
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AFNI Message Board
Hi,
thank you for your scripting suggestions, much appreciated.
Let me provide some further background to answer your question.
The input ROIs stem from the 1000 parcellation Schaefer-Yeo 17 networks recently updated by you guys:
My aim was to use the 1000 parcellations, and then to individually combine the single ROIs/parcellations into the 17 networks. There are a couple of textfi
by
Philipp
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AFNI Message Board
Hi,
I usually use 3dcalc to combine several ROIs into one ROI, such as via the following code:
3dcalc \
-a 1.nii \
-b 2.nii \
-c 3.nii \
-expr 'step(a+b+c)' \
-prefix Network.nii
But how can I combine 60, 100, or even 400 ROIs into one ROI using AFNI? Even if that was possible with 3dcalc, and as I understand it is not, writing 400 lines of code is prone to errors. What w
by
Philipp
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AFNI Message Board
Hi Paul,
Question 1: Thanks for the clarification. I was already thinking if that might be an issue due to the typical signal dropout in T2 fMRI scanning.
Question 2: You wrote that "In your case, this looks like a "false positive" at the edge of the mask". This is good to know because in the three subjects where this problem occured, it always showed up at the very side
by
Philipp
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AFNI Message Board
The preprocessing by AFNI proc is now ready and the alignment results look good. Regarding alignment, I used the raw functional scans as suggested by you and the following options:
-align_opts_aea -cost lpc+zz -giant_move \
-align_unifize_epi local \
Two more question came up.
Question 1:
When checking the "MNI152 2009 template SSW.nii.gz" underlay vs. "full_mask.subjec
by
Philipp
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AFNI Message Board
I don't have additional files, no. Is it an option to define the TR as I did with 3drefit, or do I run into problems doing this?
by
Philipp
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AFNI Message Board
This is the output of the code that you provided for the raw functional scan:
N-1 header file 'task-eoec_bold.nii.gz', num_fields = 1
name offset nvals values
------------------- ------ ----- ------
pixdim 76 8 -1.0 3.203125 3.203125 3.2 0.0 0.0 0.0 0.0
And this is the output of 3dinfo for the exact same file:
Identifier Cod
by
Philipp
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AFNI Message Board
The TR of the functional runs is 2.27 s. The raw .nii files display a TR of 1 s when inspecting them with 3dinfo.
If I simply preprocess these raw functional runs with AFNI proc, the AFNI proc HTML QC page still displays a TR of 1 s.
Hence, I changed the TR from 1 to 2.27 s using 3drefit. The 3drefit output functional runs are now forwarded to AFNI proc with the settings you suggested.
S
by
Philipp
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AFNI Message Board
I am very surprised that AFNI proc can or should handle the oblique functional runs without previously applying 3drefit’s -deoblique and -oblique_recenter options. Thats because in the past I often faced alignment problems with such oblique datasets. But I will try it out right now, only applying 3drefits TR option to change the TR. Thanks for your help so far!
by
Philipp
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AFNI Message Board
Hi,
thanks and you are right, I made a mistake. Here is the anatomial-functional overlap between raw T1 and raw EPI.
The image shows the output of @djunct_overlap_check.
# ulay = t1w.nii.gz
# ulay_is_obl = 0
# ulay_obl_ang = 0.000
# mat44 Obliquity Transformation ::
1.000000 -0.000000 0.000000 0.000000
0.000000 1.000000 0.000000 0.
by
Philipp
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AFNI Message Board
Hi Paul,
here is the output of
@djunct_overlap_check \
-ulay DSET_ANATOMICAL \
-olay DSET_EPI \
-prefix img_epi_anat_olap
for the same subject that I showed before. Please see the first attached image. I am not sure if that overlap is good enough. The problem is that AFNI proc alignment fails (note that the SSwarper results are really clean and nice, so the problem is not comming f
by
Philipp
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AFNI Message Board
Hi Paul,
QuoteWhen you say that you get "bad results", what does that mean---if you put your recentered data into afni_proc.py, is the EPI-anatomical alignment not good (ve2a block), or is the anatomical-template alignment not good (va2t block)?
By "bad results" I refered to the new or lower image attached, that is, the result of 3drefit (and not a preprocessed result by
by
Philipp
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AFNI Message Board
Hello,
I have a dataset with very oblique functional runs for almost all subjects. The first/upper image below shoes the original (raw data) anatomical-functional overlap.
Then, I ran 3drefit on both the anatomical and functional scans as follows:
3dcopy $directory_raw/anat/T1w.nii.gz Temporary
3drefit -oblique_recenter Temporary+orig
3drefit -deoblique Temporary+orig
3dcopy Tempora
by
Philipp
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AFNI Message Board
Thank you Gang.
This is for you:
directory_results=volumes/GangChanFanClub
3dPaulaner \
-3dcopy Paulaner \
-prefix directory_results/Paulaner+tlrc \
by
Philipp
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AFNI Message Board
Hello,
I am using z shell (zsh) on a Mac. I am trying to run 3dISC after computing pairwise correlations between subjects using 3dTcorrelate.
The problem is that 3dISC prints the following error after I try running it.
Processing Interoception ...
updating R_LD_LIBRARY_PATH ...
** Error:
The content under -dataTable is not rectangular ! 761 3
Processing Exteroception ...
updat
by
Philipp
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AFNI Message Board
Hi,
just to confirm again:
-1Dfile ename Save the motion parameters ONLY in file 'ename'.
The output is in 6 ASCII formatted columns:
roll pitch yaw dS dL dP
Hence, column 1 starts with roll and column 6 ends with dP. Correct?
I am asking this again because if I use the following code:
Results 1dplot -volreg dfile_rall.1D
by
Philipp
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AFNI Message Board
Hi Rick,
the Pearson correlation is computed in Python using the two extracted AFNI data lists that stem from the two computed variables.
This means that two giant lists of voxels are correlated against each other, yielding one correlation result.
You are right insofar as one could also correlate the data already in AFNI using 3dTcorrelate. The number of voxels (numeric values) per file wo
by
Philipp
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AFNI Message Board
Hi Paul,
oh yes, you are right. The error should stem from 1dcat and not from 3dmaskdump.
As I understand you, the problem stems from a limitation of the code for handling .1D files. It is not a bug, just a "limitation" so to speak.
You asked for the reason why I play around with such a massive amount of voxels. I have two ROIs which span across the whole cerebral cortex. Consequ
by
Philipp
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AFNI Message Board
Hi,
I am trying extract voxel-based numeric values into .1D and .txt files using 3dmaskdump.
The extraction works fine for all ROIs except for one. The ROI where 3dmaskdump fails also has the highest voxel number (compared to the other ROIs), and I assume this is the reason why 3dmaskdump fails with the following message.
**Error: Line too long for buffer of 5048576 chars.** ERROR: mri
by
Philipp
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AFNI Message Board
Dear AFNI people (and dear Paul),
I have a question concerning the Lomb-Scargle Periodogram and its AFNI implementation, namely 3dLombScargle.
The number of bins in the frequency-domain that are created by 3dLombScargle are defined by 1/T, where T is the duration or number of sampling points of the time-series (in TRs, I assume).
Is there a way to change the number of bins, like in a sta
by
Philipp
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AFNI Message Board
QuoteYou mention having "5xx sampling points"---does that mean you upsampled by a factor of 5?
I did not remember the exact number of TRs, therefore I simply wrote "5xx", because I have 500 something TRs in one run. I did not upsample the time-series for different reasons, one of them because the upsampling would make them more linear. Sorry for the confusion.
QuoteNote
by
Philipp
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AFNI Message Board
Paul, thanks.
Let me ask you a further question to maybe solve this and provide you with more details.
Some facts first.
- The preprocessed time-series (the .errts file) is given to 3dPeriodogram.
- 3dPeriodogram creates the power spectrum (no tapering, nfft=1024, time-series has 5xx sampling points).
- 3dTcat then cuts the output by 3dPeriodogram to my desired frequency range, i.e., it
by
Philipp
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AFNI Message Board
Hi Paul,
thank you a lot for the elaborate explanation! See my replies below.
QuoteSo, neither of the programs involve logs---that is not an issue here (you can take log after).
Correct. This is why I showed the power spectra (and not their log-log version) in my first post. The “problem” (the difference in power) has nothing to do with the log, but is already present in the standard pow
by
Philipp
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AFNI Message Board
Hi Paul,
the first question would be: what do 3dPeriodogram and 1dFFT really compute – magnitude or power, as you say?
Do they compute magnitude on the y-axis, so that I have to square their results (^2) or (**2 in Python) to get power?
The description of 3dPeriodogram says:
The result is the squared magnitude of the FFT of w(k)*data(k),
divided by P. This division makes the result
by
Philipp
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AFNI Message Board
Dear all,
after using 3dPeriodogram for a longer time now, I stumbled across a strange “problem”. I am interested in computing power spectra and additionally I am interested in computing the slope of a linear regression in the log-frequency log-power transformation of the frequency-domain, namely the power-law exponent (PLE).
Here are two options how to accomplish this, while option 1 is cl
by
Philipp
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AFNI Message Board
Paul, you summed the lines over lines of my question up into one sentence: “is the quality of fitting in the first 400 time points different than that of the remaining ones, such that the residuals would have very different properties?”.
Thanks for this one. :D
This is basically what I was thinking about. Normally, I don't use bandpassing and leave the polort option to the automatic s
by
Philipp
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AFNI Message Board
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