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001014462 005__ 20231013201849.0
001014462 0247_ $$2doi$$a10.1101/2023.06.21.545953
001014462 0247_ $$2datacite_doi$$a10.34734/FZJ-2023-03312
001014462 037__ $$aFZJ-2023-03312
001014462 041__ $$aEnglish
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001014462 1001_ $$0P:(DE-HGF)0$$aBalan, Puiu F$$b0$$eCorresponding author
001014462 245__ $$aMEBRAINS 1.0: a new population-based macaque atlas
001014462 260__ $$aCold Spring Harbor$$bCold Spring Harbor Laboratory, NY$$c2023
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001014462 520__ $$aDue to their fundamental relevance, the number of anatomical macaque brain templates is constantly growing. Novel templates aim to alleviate limitations of previously published atlases and offer the foundation to integrate multiscale multimodal data. Typical limitations of existing templates include their reliance on one subject, their unimodality (usually only T1 or histological images), or lack of anatomical details. The MEBRAINS template overcomes these limitations by using a combination of T1 and T2 images, from the same 10 animals (Macaca mulatta), which are averaged by the multi-brain toolbox for diffeomorphic registration and segmentation. The resulting volumetric T1 and T2 templates are supplemented with high quality white and gray matter surfaces built with FreeSurfer. Human-curated segmentations of pial surface, white/gray matter interface and major subcortical nuclei were used to analyse the relative quality of the MEBRAINS template. Recently published 3D maps of the macaque inferior parietal lobe and (pre)motor cortex were warped to the MEBRAINS surface template, thus populating it with a parcellation scheme based on cyto- and receptor architectonic analyses. Finally, 9 CT scans of the same monkeys were registered to the T1 modality and co-registered to the template. Through its main features (multi-subject, multi-modal, volume-and-surface, traditional and deep learning-based segmentations), MEBRAINS aims to improve integration of multi-modal multi-scale macaque data and is quantitatively equal or better compared to currently widely used macaque templates. The template is integrated in the EBRAINS and Scalable Brain Atlas web-based infrastructures, each of which comes with its own suite of spatial registration tools.
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001014462 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x2
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001014462 7001_ $$0P:(DE-HGF)0$$aZhu, Qi$$b1
001014462 7001_ $$0P:(DE-HGF)0$$aLi, Xiaolian$$b2
001014462 7001_ $$0P:(DE-Juel1)171512$$aNiu, Meiqi$$b3
001014462 7001_ $$0P:(DE-Juel1)176736$$aRapan, Lucija$$b4
001014462 7001_ $$0P:(DE-Juel1)181092$$aFunck, Thomas$$b5$$ufzj
001014462 7001_ $$0P:(DE-Juel1)145578$$aBakker, Rembrandt$$b6$$ufzj
001014462 7001_ $$0P:(DE-Juel1)131701$$aPalomero-Gallagher, Nicola$$b7$$ufzj
001014462 7001_ $$0P:(DE-HGF)0$$aVanduffel, Wim$$b8
001014462 773__ $$0PERI:(DE-600)2766415-6$$a10.1101/2023.06.21.545953$$tbioRxiv beta$$y2023
001014462 8564_ $$uhttps://juser.fz-juelich.de/record/1014462/files/Balan_etal_MEBRAINS_2023_preprint.pdf$$yOpenAccess
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001014462 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU 6 Leuven Medical School, 3000 Leuven, Belgium$$b0
001014462 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$aLaboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU 6 Leuven Medical School, 3000 Leuven, Belgium, Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris-Saclay, NeuroSpin 8 Center, 91191 Gif/Yvette, France$$b1
001014462 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, 3000 Leuven, Belgium$$b2
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001014462 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU 6 Leuven Medical School, 3000 Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Harvard Medical School, Boston, MA 02144, USA$$b8
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001014462 9141_ $$y2023
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