MEBRAINS 1.0: a new population-based macaque atlas

Balan, Puiu F; Bakker, Rembrandt; Vanduffel, Wim; Niu, Meiqi; Funck, Thomas; Li, Xiaolian; Palomero-Gallagher, Nicola; Zhu, Qi; Rapan, Lucija

doi:10.1101/2023.06.21.545953

Preprint

FZJ-2023-03312

MEBRAINS 1.0: a new population-based macaque atlas

Balan, P. F. (Corresponding author) ; Zhu, Q. ; Li, X. ; Niu, M.FZJ* ; Rapan, L.FZJ* ; Funck, T.FZJ* ; Bakker, R.FZJ* ; Palomero-Gallagher, N.FZJ* ; Vanduffel, W.

2023
Cold Spring Harbor Laboratory, NY Cold Spring Harbor

bioRxiv beta (2023) [10.1101/2023.06.21.545953]

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Please use a persistent id in citations: doi:10.1101/2023.06.21.545953 doi:10.34734/FZJ-2023-03312

Abstract: Due to their fundamental relevance, the number of anatomical macaque brain templates is constantly growing. Novel templates aim to alleviate limitations of previously published atlases and offer the foundation to integrate multiscale multimodal data. Typical limitations of existing templates include their reliance on one subject, their unimodality (usually only T1 or histological images), or lack of anatomical details. The MEBRAINS template overcomes these limitations by using a combination of T1 and T2 images, from the same 10 animals (Macaca mulatta), which are averaged by the multi-brain toolbox for diffeomorphic registration and segmentation. The resulting volumetric T1 and T2 templates are supplemented with high quality white and gray matter surfaces built with FreeSurfer. Human-curated segmentations of pial surface, white/gray matter interface and major subcortical nuclei were used to analyse the relative quality of the MEBRAINS template. Recently published 3D maps of the macaque inferior parietal lobe and (pre)motor cortex were warped to the MEBRAINS surface template, thus populating it with a parcellation scheme based on cyto- and receptor architectonic analyses. Finally, 9 CT scans of the same monkeys were registered to the T1 modality and co-registered to the template. Through its main features (multi-subject, multi-modal, volume-and-surface, traditional and deep learning-based segmentations), MEBRAINS aims to improve integration of multi-modal multi-scale macaque data and is quantitatively equal or better compared to currently widely used macaque templates. The template is integrated in the EBRAINS and Scalable Brain Atlas web-based infrastructures, each of which comes with its own suite of spatial registration tools.

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