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Dear AFNI experts,
I just tested the new version of animal_warper. Everything works fine, but I just find something not normal when the bain mask is produced at the end. I guess it is based on the skullstriped anatomical image in the template space that is sent back into the subject space? It seems that the mask is cut when compared to the previous version. In consequence, in macaque, I am losi
by
Doughboys
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AFNI Message Board
Hi AFNI expert,
is it still not possible to performed VBM with AFNI?
if not, can I use (SPM, ANTS, or something else) to calculate the voxel-wise volume ratio changes after using @animal_warper?
Thanks a lot!
Clément
by
Doughboys
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AFNI Message Board
Hi -pt,
Sorry to come back with this old topic but my new problem is actually related to the co-registration of these animals.
By having a deep look at the co-registrated functional images and extracting some signal with the D99 atlas, I finally understand why the correlation coefficients were not great.
It seems that a slight section of voxels in the grey matter (edge) of the functional
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Doughboys
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AFNI Message Board
Salut pt,
No problem I will send you that straight away.
Tks!
Clément
by
Doughboys
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AFNI Message Board
Hello AFNI experts
I would like to use a macaque atlas that is in the F99 template space.
In order to do that, I would like to send the atlas in the nmt template.
To do so I used:
@animal_warper -input nmt_1.2/NMT_SS.nii.gz -base Human_macaque_equivalent/F99_with_skull.nii.gz -atlas RM_inF99.nii.gz -outdir Human_macaque_equivalent/InD99 -skullstrip Human_macaque_equivalent/F99_with_sku
by
Doughboys
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AFNI Message Board
Dear AFNI expert,
I am trying to coregistrate fMRI images to their anatomical and then to a Template for another species (mouse lemur) and with afni_proc.py
To do so, I applied the exact same script as described here for macaques:
I am using a template that we published:
In order to use the script and afni_proc.py, I had to change the template space name to NMT but I guess that is
by
Doughboys
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AFNI Message Board
Hi, Pt-
First, thank you for your answer,
I have done the analysis and:
Re. "Since I increase the number of regions and so the number of subdivisions in each atlas I may expect a relatively linear increase of the mean ReHo for each atlas?"*
Re. "Does this will really identify an atlas that could be 'ideal' for a correlation matrix analysis?"
--Yes, the incre
by
Doughboys
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AFNI Message Board
Hello AFNI expert,
I would like to compare the ability of different atlases to extract a homogeneous BOLD signal in each ROI.
I created different atlases based on ICA. I built one atlas per component number (for ex: from 5 to 30 components so I have 25 atlases).
I was thinking of using 3dReHo with -in_rois one each atlas and calculating the curve of an increase of ReHo per atlas.
Since I
by
Doughboys
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AFNI Message Board
Hi Gang,
Thank you again for your answer,
For the record, here is the new command:
3dLME -prefix /3dLME_glt.nii.gz \
-jobs 8 -model "gender*age" -qVars "age" -ranEff '~1+age' \
-num_glt 5 \
-gltLabel 1 '05MF' -gltCode 1 'gender : 0.5*M +0.5*F age :' \
-gltLabel 2 '1MF' -gltCode 2 'gender : 1*M -1*F age :' \
-gltL
by
Doughboys
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AFNI Message Board
Hi Gang,
Thank you again for your help!!
As advised, I ran the command:
3dLME -prefix 3dLME_.nii.gz -jobs 8 \
-model "gender*age" \
-qVars "age" \
-ranEff '~1+age' \
-dataTable
Subj age Sexe InputFile
Oliver 1128.0 M /Oliver2019_02_02_ztest.nii.gz \
Oliver 1247.0 M Oliver2019_06_01_ztest.nii.gz \
Oliver 1353.0 M Oliver2019_09_15_ztest.nii.gz \
Oliv
by
Doughboys
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AFNI Message Board
Hi Gang,
Thank for your answer!
The subjects were not measured exactly at the same age but within the same session. The effect of interest is the age and I am looking to observe a correlation with the modification of the connectivity strength. As an example, I previously did an extraction of the ALLF signal with an atlas and then calculated the Repeated measures correlation coefficient within
by
Doughboys
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AFNI Message Board
Hello AFNI experts in statistics,
I would like to measure the effect on age on a longitudinal fMRI resting-state dataset (4 repeated measures at a different age) with covariate such has gender.
I already performed the seed base analysis on each subject and now I want to regress the age on each statistical maps in order to observe the age related variation of the DMN connectivity (with gen
by
Doughboys
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AFNI Message Board
Hi AFNI expert,
I finally found the solution and I will probably be able to be more clear.
Two things were impacting the results of this analysis and fixing it has tremendously improved the quality of the coregistration:
1. Deobliquing the data prior to @afni_proc.py can be dangerous if like in my dataset the EPI and the anatomical images have different FOV orientations.
3drefit
by
Doughboys
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AFNI Message Board
Hi --pt,
So sorry for the confusion,
1. The first group of monkeys (including the image that I send to you) has successfully ended. All the images are well aligned with the template (thank you again!) using the protocol that I describe here:
2. I have a second group of monkey that has been scan with another coil. For almost all these 8 monkeys, the coregistration between the functional
by
Doughboys
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AFNI Message Board
Hi again,
sry I am probably not clear at all and I hope that I am not looking in the wrong direction.
The result from your previous command is:
anat
RAI -61.685852 65.814148 -30.202454 97.297546 7.62584587.125847 anatT1.nii.gz
func
RAI -62.152084 63.847916 -21.139194 104.861847 -6.759480 55.241032 BOLD_restingstate.nii.gz
after tranfo:
RAI -62.152084 63.847916 -21.139194 104.861847 -6.7
by
Doughboys
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AFNI Message Board
Hi --pt,
Thank you, I don't think that it is going to work because in the previous pipeline we already align the center of these two images.
I think that the problem comes from the fact that the two images do not overlay.
Probably, when we apply the transformation parameters, they can't be accurate anymore because the orientation of the two brains is different.
The non-overlay of
by
Doughboys
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AFNI Message Board
Hi --pt,
If we go back to what we have done here:
# --------------------- for obliquity and center of mass of EPI
3dcalc \
-a ${dset_bold} \
-expr 'a' \
-prefix ${dset_bold_deob}
# purge obliquity info, and apply shifts so BOLD dset overlays anat dset well
3drefit \
-deoblique
by
Doughboys
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AFNI Message Board
Hi AFNI expert,
I have 1 anatomical image and 1 functional image that has been acquired with two different FOV orientations.
When I use different viewer (AFNI, MRIcron) the images superposed perfectly because (I don't know where but the orientation of the FOV is saved somewhere)
I have to do some manipulation on the images (obliquity, change the centre etc...) and this orientation is
by
Doughboys
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AFNI Message Board
Hello AFNI,
Thanks to --pt I have now the solution for the coregistration of the functional images in macaques:
I had difficulty with nonlinear warping because large shifts were involved:
"basically, the memory usage can be quite high, because the warp field must cover a box that covers both input and output datasets-- and a large shift means that one would need a large box (memory c
by
Doughboys
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AFNI Message Board
Ok, I find a way to do it but I don't know why...
based on the idea that the transformation from 3dNwarpApply was false...
# apply catenated xform: volreg/epi2anat/tlrc/NLtlrc
# then apply non-linear standard-space warp
3dNwarpApply -master anatT1_deob_warp2std_nsu+tlrc -dxyz 2 \
-source pb01.$subj.r$run.tshift+orig \
by
Doughboys
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AFNI Message Board
Hi ptaylor,
Here is the command after @animal_warper
# afni_proc.py -subj_id Oliver2019_02_02 -script \
# /8_Func_AFNI/Oliver2019_02_02/proc.Oliver2019_02_02 \
# -scr_overwrite -out_dir \
# /8_Func_AFNI/Oliver2019_02_02/Oliver2019_02_02.results \
# -blocks tshift a
by
Doughboys
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AFNI Message Board
Hi ptaylor,
Thank you so much for your help!
+ the original coordinates are a bit odd-- while the anatomical and EPI overlay each other, the (x, y, z) = (0, 0, 0) location is far outside the brain; this can affect some alignment issues.
==> Do you have any idea of what could cause that in the aquisiton protocol?
I applied strictly your protocol, and it has improved the co registration
by
Doughboys
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AFNI Message Board
I think also that sharing this images could be the easiest solution. Thank you so much for your help!
Clément
by
Doughboys
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AFNI Message Board
Thank you again!
With pleasure! will let you know when I will start my work on other species.
The 3drefit on warp2std_nsu.nii.gz did a perfect job, to change the space and it has allow afni_proc to continu.
However, when it arrived to
# apply catenated xform: volreg/epi2anat/tlrc/NLtlrc
# then apply non-linear standard-space warp
3dNwarpApply -master anatT1_warp2std_nsu+
by
Doughboys
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AFNI Message Board
Great thank you so much for that!
So which template do you suggest to use? or is there a way to bypass this issu directly in afni_proc and work with the ORIG space?
Maybe I don't understand afni_proc very well, is it totally necessary to have a template in the tlrc space? because I the futur I would like to work with other species and a home made template. Do you think that it will be poss
by
Doughboys
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AFNI Message Board
Hi again,
I downloaded the template at:
3dinfo NMT_SS.nii.gz
Identifier Code: AFN_ZuEbKDcZ-wbFK6dSTdvAsQ Creation Date: Wed Apr 26 15:47:32 2017
Template Space: ORIG
Dataset Type: Anat Bucket (-abuc)
Byte Order: LSB_FIRST {assumed}
Storage Mode: NIFTI
Storage Space: 86,035,180 (86 million) bytes
Geometry String: "MATRIX(-0.25,0,0,31.75,0,-0.25,0,50.5,0,0,0.2
by
Doughboys
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AFNI Message Board
Hi again,
I downloaded the template at:
3dinfo NMT_SS.nii.gz
Identifier Code: AFN_ZuEbKDcZ-wbFK6dSTdvAsQ Creation Date: Wed Apr 26 15:47:32 2017
Template Space: ORIG
Dataset Type: Anat Bucket (-abuc)
Byte Order: LSB_FIRST {assumed}
Storage Mode: NIFTI
Storage Space: 86,035,180 (86 million) bytes
Geometry String: "MATRIX(-0.25,0,0,31.75,0,-0.25,0,50.5,0,0,0.2
by
Doughboys
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AFNI Message Board
Hi again,
I downloaded the template at:
3dinfo NMT_SS.nii.gz
Identifier Code: AFN_ZuEbKDcZ-wbFK6dSTdvAsQ Creation Date: Wed Apr 26 15:47:32 2017
Template Space: ORIG
Dataset Type: Anat Bucket (-abuc)
Byte Order: LSB_FIRST {assumed}
Storage Mode: NIFTI
Storage Space: 86,035,180 (86 million) bytes
Geometry String: "MATRIX(-0.25,0,0,31.75,0,-0.25,0,50.5,0,0,0.2
by
Doughboys
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AFNI Message Board
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