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Dataset Open Access

RheMAP: Non-linear warps between common rhesus macaque brain templates

Nikoloz Sirmpilatze; P. Christiaan Klink

General description. This dataset contains a set of non-linear registration warps between some of the most commonly used rhesus macaque brain templates (D99, INIA19, MNI macaque, NMT, Yerkes19). Non-linear registration warps were generated using ANTs. The code used to generate the warps and example code on how to use them to remap data between different standard spaces is available on GitHub as RheMAP (doi 10.5281/zenodo.3673082). The actual templates are not included in this dataset since redistribution is often not allowed. Links to there sources can be found in the documentation of RheMAP

Rationale. Group analysis of (f)MRI data is commonly performed in a standard template space to which individual data is registered. The choice and adoption of such a standard space is becoming especially relevant now that data sharing initiatives make it much more feasible to obtain larger sample sizes. For human fMRI, the MNI template provides a widely adopted standard space. For non-human fMRI, widely adopted standard templates are often lacking. In 2018, the PRIME-DE (PRIMatE Data Exchange) consortium launched a platform for the exchange of non-human primate MRI data. The initiative was expanded in 2020 with PRIME-RE (PRIMatE Resource Exchange) that aims to provide a portal to analysis approaches related to the non-human primate MRI. Since the generation of non-linear registrations between different brains is a timely and computationally heavy operation, we have created a set of non-linear registration warps that allow the direct remapping of (f)MRI data across different common template brains. Since the code for this approach is also provided, the set can easily be expanded to include additional template brains.

Code. All code and extensive documentation is available on GitHub as RheMAP. The RheMAP repository is also archived by Zenodo under doi 10.5281/zenodo.3673082.

Data structure. The data is provided both as a directory structure compressed as all_the_data.zip (preferred way) and as individual files. The correspondence between the directory structure and the individual files is contained in the file tree.json (uploaded as tree.json.txt due to issues with the Zenodo uploader). The bash command source unflatten.sh can be used to convert the individual files into the original directory structure. The warps/linear folder contains the affine registration, the warps/nonlinear folder contains the nonlinear warps of the already linearly aligned volumes, and the warps/final folder contains the full warps across templates. Similarly, the warped_templates/linear folder contains the results of the affine registration, the warped_templates/nonlinear folder contains the results of the nonlinear registration of the already linearly aligned volumes, and the warped_templates/final folder contains the results of all final template-to-template registrations (linear + non-linear).

Diagnostic images. A set of diagnostic images is included for quality control and visual inspection of the results: 

  • 00_RegisterTemplates.pdf outlines the general approach.
  • 01_Templates.pdf displays the included template brains.
  • 02_Linear_reg.pdf outlines gives the results of linear alignment.
  • 03x_<TEMPLATE>_pairs.pdf gives the results of the final alignment of <TEMPLATE> with all other templates (two directions).

Acknowledgements. This project was initiated at the Brainhack: Comparative MRI event in London (September 2019), following the PRIME-DE Global Collaboration Workshop.

Citation. Sirmpilatze, N. and Klink, P.C. (2020). RheMAP: Non-linear warps between common rhesus macaque brain templates (Version 1)[Data set]. Zenodo. https://doi.org/10.5281/zenodo.3668510

Files (24.4 GB)
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00_RegisterTemplates.pdf
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01_Templates.pdf
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02_Linear_reg.pdf
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03a_D99_pairs.pdf
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03b_INIA_pairs.pdf
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03c_MNI_pairs.pdf
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03d_NMTv1.2_pairs.pdf
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03e_NMTv1.3_pairs.pdf
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03f_YRK_pairs.pdf
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all_the_data.zip
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flatten.sh
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tree.json
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unflatten.sh
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warps_final_INIA_to_D99_CompositeWarp.nii.gz
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warps_final_INIA_to_MNI_CompositeWarp.nii.gz
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warps_linear_D99_to_INIA_affine_0GenericAffine.mat
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warps_linear_D99_to_MNI_affine_0GenericAffine.mat
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warps_linear_D99_to_YRK_affine_0GenericAffine.mat
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warps_linear_INIA_to_MNI_affine_0GenericAffine.mat
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warps_linear_INIA_to_YRK_affine_0GenericAffine.mat
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