Atlases Hub
Version5 - Released in 2023

The Version-5 Focused on the Marmoset Cerebellum

Zhu, et al. An Anatomical and Connectivity Atlas of the Marmoset Cerebellum. 2023

Abstract The cerebellum is essential for motor control and cognitive functioning, engaging in bidirectional communication with the cerebral cortex. The common marmoset, a small non-human primate, offers unique advantages for studying cerebello-cerebral circuits. However, the marmoset cerebellum is not well-described in published resources. In this study, we present a comprehensive atlas of the marmoset cerebellum, comprising: 1) fine-detailed anatomical atlases and surface-analysis tools of the cerebellar cortex based on ultra-high resolution ex-vivo MRI; 2) functional connectivity and gradient patterns of the cerebellar cortex revealed by awake resting-state fMRI; and 3) structural-connectivity mapping of cerebellar nuclei using high-resolution diffusion MRI tractography. The atlas elucidates the anatomical details of the marmoset cerebellum, reveals distinct gradient patterns of intra-cerebellar and cerebello-cerebral functional connectivity, and maps the topological relationship of cerebellar nuclei in cerebello-cerebral circuits.

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Version4 - Released in 2022

The Version-4 Focused on Awake Resting-state Functional Connectivity

Tian X, et al. A integrated resource for functional and structural connectivity of the marmoset brain. 2021

Abstract Comprehensive integration of the structural and functional connectivity data is a requirement for accurate modeling of brain functions. While resources for charting the marmoset structural connectivity already exist, open data and tools for functional brain mapping are still unavailable. Here, we present the most comprehensive resource for non-human primate brain mapping, which integrates the largest awake resting-state test-retest fMRI dataset (39 marmosets, 709 runs, and 12053 mins), cellular-level neuronal-tracing dataset (52 marmosets, and 143 injections), and multi-resolution diffusion MRI dataset. The combination of these data into the same stereotaxic space allowed us: 1) mapping the fine-detailed functional networks and cortical parcellations; 2) developing a deep-learning-based parcellation generator to preserve the topographical organization of functional connectivity and reflect individual variabilities; 3) investigating the structural basis underlying functional connectivity by computational modeling. Therefore, our resource will broadly model the marmoset brain architecture and facilitate future comparative and translational studies of primate brains.

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Version3 - Published in 2021

The Version-3 Focused on Population-based Standard Templates

Liu C, et al. Marmoset Brain Mapping V3: Population multi-modal standard volumetric and surface-based templates. 2021

Abstract The standard anatomical brain template provides a common space and coordinate system for visualizing and analyzing neuroimaging data from large cohorts of subjects. Previous templates and atlases for the common marmoset brain were either based on data from a single individual or lacked essential functionalities for neuroimaging analysis. Here, we present new population-based in-vivo standard templates and tools derived from multi-modal data of 27 marmosets, including multiple types of T1w and T2w contrast images, DTI contrasts, and large field-of-view MRI and CT images. We performed multi-atlas labeling of anatomical structures on the new templates and constructed highly accurate tissue-type segmentation maps to facilitate volumetric studies. We built fully featured brain surfaces and cortical flat maps to facilitate 3D visualization and surface-based analyses, which are compatible with most surface analyzing tools, including FreeSurfer, AFNI/SUMA, and the Connectome Workbench. Analysis of the MRI and CT datasets revealed significant variations in brain shapes, sizes, and regional volumes of brain structures, highlighting substantial individual variabilities in the marmoset population. Thus, our population-based template and associated tools provide a versatile analysis platform and standard coordinate system for a wide range of MRI and connectome studies of common marmosets.

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Version2 - Published in 2020

The Version-2 Focused on White Matter Pathways


Liu C, et al. A resource for detailed 3D mapping of white matter pathways in the marmoset brain. Nature Neuroscience. 2020

Abstract While the fundamental importance of the white matter in supporting neuronal communication is well known, a detailed description of its complex anatomy is not prominently featured in existing publications of primate brains. One main barrier is that existing neuroimaging data of the primate brain have either insufficient spatial resolution or image contrast to fully resolve white matter pathways. Here, we present an open resource that allows detailed descriptions of white matter structures and the trajectory of fiber-pathways in the marmoset brain. The resource includes 1) diffusion MRI (dMRI) data with the highest resolution available to date revealing white matter features never previously described; 2) a comprehensive 3D white matter atlas depicting fiber pathways that were either omitted or misidentified in previous atlases; 3) comprehensive fiber-pathway maps of cortical connections combining dMRI tractography and neuronal tracing data. Our data will facilitate studying brain connectivity and developing tractography algorithms in the primate brain.

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Online-viewing Tracing-guided Tracking Probilities Maps Online-viewing the Merged Atlas (v2.0.1) with cortex_vH Online-viewing the Merged Atlas (v2.0.1) with cortex_vPaxinos
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Version1 - Published in 2018

The Version-1 Focused on Cortical Parcellations


Liu C, et al. A digital 3D atlas of the marmoset brain based on multi-modal MRI. Neuroimage. 2018

Abstract The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets.

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