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Establishes a multimodal brain atlas in rabbits, suggesting advancements for neuroscience research.
The rabbit serves as a critical bridge species in translational neuroscience due to its human-like neurodevelopmental trajectories, white matter architecture, and biophysical neuronal properties. However, the lack of a standardized, high-resolution in vivo brain atlas has significantly impeded its broader adoption in systems neuroscience and disease modeling. In this study, we established a multimodal, population-averaged in vivo template and stereotaxic framework for the adult New Zealand White rabbit by integrating 5.0 T in vivo MRI, 9.4 T ex vivo MRI, and micro-CT imaging. Using multi-contrast priors, we systematically identified 107 fine-grained regions across the cortex, white matter, and subcortical structures. To facilitate broad accessibility, we developed a deep learning-based pipeline that enables fully automated whole-brain segmentation, eliminating the need for manual preprocessing. Our results demonstrate that this atlas effectively captures native anatomical states, overcoming the tissue deformation inherent in legacy ex vivo templates. With a fully differentiated striatum and a brain volume sixfold larger than that of rodents, this framework provides a superior platform for translational brain disease research and longitudinal functional imaging. By providing a publicly available, anatomically accurate reference, this work establishes a standardized foundation for neuroscientific research across the evolutionary continuum.
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Zhanbo et al. (2026) studied this question.
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