I have done all my preprocessing and level-1 analyses using the MNI152NLin6Asym_res-02 template. Then, I created a ROI mask with fsleyes by extracting a brain region according to the Juliech built-in atlas.
My problem is that, to my understanding, the Juliech atlas is built in the symmetric linear MNI152 space (i.e., MNI152_T1_2mm), which is slightly different than the non-linear space I used.
Is there a Juliech atlas adapted to the MNI152NLin6Asym_res-02 template?
Alternatively, I can use the applywarp command to transform my mask from one space to another. How do I get the warp file (i.e., the transformation coordinates) to transform from the ROI in standard MNI1522mm to a ROI in the MNI152NLin6Asym_res-02 template?
Isn’t the Juliech atlas present in FSL, which would mean that it is defined in the MNI space from FSL, i.e. the MNI152NLin6 Asym space?
FSL says the following:
The atlas contains 52 grey matter structures and 10 white matter structures. This is an update to the data used in Eickhoff’s Anatomy Toolbox v1.5. The atlas is based on the miscroscopic and quantitative histological examination of ten human post-mortem brains. The histological volumes of these brains were 3D reconstructed and spatially normalised into the space of the MNI single subject template to create a probabilistic map of each area. For the FSL version of this atlas, these probabilistic maps were then linearly transformed into MNI152 space.
I have been trying to make the most recent versions of the JulichBrain maps available in AFNI, so I am working with that group at Julich under Katrin Amunts to get that done. While I’m not sure about the FSL version, I believe that the JulichBrain 2.9 and now 3.0, distributed through the eBrains site, are the first versions available in MNI 2009c asymmetric template space. The Julich group also makes versions of the atlas that are compatible with the MNI-N27 brain too.
The previous versions that had been distributed with the SPM anatomy toolbox (“cytoarchitectonic Eickhoff-Zilles atlases”) were in various spaces depending on the version from the original MNI-152, the 2006 MNI nonlinear template space or the N27 brain in MNI space, but these were typically shifted away from the standard MNI space along two axes (MNI_ANAT space in AFNI-speak). The differences among the various MNI templates are not obvious, and it’s tricky to notice for atlases that have only partial brain coverage.
The atlas is undergoing some changes, but this link provides a kind of alpha/beta release version.
I am sorry to go back to this point, but the problem is that when I look in fsleyes on the MNI152NLin6sym_brain file and the Juliech ROI mask, I get the warning “displaying images with different orientations/fields of view!”. In contrast, when I upload the MNI_152_T1_2mm_brain file together with the ROI, I don’t get this warning. This makes me think that there still a bit of a difference between the ROI template and the asymmetric non-linear template (although they look almost identical).
Where did you get the Julich ROI mask and the MNI152NLin6sym_brain files?
If you wants to use the MNI152NLin6Asym space, I would rather use the Julich atlas files given from FSL.
Also, the resource pointed out by @dglen is interesting. Perhaps you could use the most recent version of the Juliech atlas defined in MNI152NLin2009cAsym space and convert it to MNI152NLin6Asym space through the transformation from template flow: tpl-MNI152NLin2009cAsym_from-MNI152NLin6Asym_mode-image_xfm.h5
@jsein - using template flow sounds like a good idea for this. The newer version of the JulichBrain is based on more subjects and has more complete brain coverage than the older versions - in general. It is missing the cerebellum atlases provided by Diedrichsen, so that would require either the older atlas with it or a separate download of the SUIT cerebellum atlas.
It looks like there is a mismatch of the atlas mask with the template, so it may have come from a different place. If it is a legitimate version or if you are using a new version, then you may need to match the orientation and grid with a resampling onto the grid of the template or onto the grid of the particular dataset for analysis.
I would be interested in performing the conversion of the Juliech atlas in the MNI152NLin2009cAsym space (downloaded from here) to the MNI152NLin6Asym space to match my fMRI data. Can you suggest me a way to do this conversion using the tpl-MNI152NLin2009cAsym_from-MNI152NLin6Asym_mode-image_xfm.h5 transformation file? In which cases I can use the tpl-MNI152NLin2009cAsym_from-MNI152NLin6Asym_mode-image_xfm.mat instead?
Sorry for my naive questions, and thank you for your help.
If I am not mistaken, tpl-MNI152NLin2009cAsym_from-MNI152NLin6Asym_mode-image_xfm.mat is an affine transform (linear transform with 12 degrees of freedom) while tpl-MNI152NLin2009cAsym_from-MNI152NLin6Asym_mode-image_xfm.h5 is a “composite” transform, including an affine and a warping field.
Thank you for showing this. I tried myself and It turns out that my answer was wrong indeed! Sorry about that!
I took the time to test myself and it turns out the command I wrote was not handling 4D images such as the Julich atlas image (at least with my AntS version). I was obliged to split the 4D image in 3D images to be able to see the output.
As for the aspect of warped template, this is due to the interpolation method chosen (LanczosWindowedSinc) which may not the best for this kind of image.
Besides, it looks like the warping field coming from tpl-MNI152NLin6Asym_from-MNI152NLin2009cAsym_mode-image_xfm.h5 composite trnasfirm does not work well. I tried to verify it by directly warping the MNI152NLin2009cAsym template to MNI152NLin6Asym template and the result is not what I expected: instead of shrinking a bit (the template MNI152NLin2009cAsym is slightly bigger than the MNI152NLin6Asym template), the warped MNI152NLin2009cAsym template was even bigger than its original size!
Finally, I was not able to use the tpl-MNI152NLin6Asym_from-MNI152NLin2009cAsym_mode-image_xfm.mat file.
Many things to understand yet in this topic!
Let’s continue testing and learning about this and hopefully we will find a solution soon!
Thank you so much for taking the time to test this. The information you provided has been extremely helpful.
In my case, by using the -d 3 and -e 3 options, antsApplyTransforms was able to handle the 4D atlas image (it applied the transform on each 3D matrix at a time, progressing along the 4th dimension). However, the important thing to know is that the tpl-MNI152NLin6Asym_from-MNI152NLin2009cAsym_mode-image_xfm.h5 is not working properly.
I’ll try to perform other conversions using the atlas in a different space, and I’ll test different interpolation methods. If anything interesting comes up, I will post an update.
Hopefully, by trial and error, we will eventually find a solution.
On the other hand, I tried to warp MNI152NLin6Asym template into MNI152NLin2009cAsymtemplate using tpl-MNI152NLin2009cAsym_from-MNI152NLin6Asym_mode-image_xfm.h5 composite transform, and this one works as expected!
One could think of inverting the transform to fit your needs but from what I read from forums, it is not feasible easily.
While I don’t know how to invert the transformation with TemplateFlow or with ANTs, it is simple to do the equivalent with AFNI.
First, with the NLin6Asym template from the TemplateFlow.org site, one can compute the affine and nonlinear transformation to align that with the 2009c template. Here just treating the NLin6 template as any other anatomical dataset for alignment:
Then apply the transformation to the desired atlas to move to be in alignment with the NLin6 template. Here I used the maximum probability map of 157 regions. To move this kind of dataset, use nearest neighbor interpolation (NN). The dataset is one that has labels in its header, so it can make use of the whereami feature and the overlay labels in AFNI. The second command below copies the labels over from the 2009c atlas to the new NLin6 atlas.