Neuronal diversity and stereotypy at multiple scales through whole brain morphometry

IF 14.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Yufeng Liu, Shengdian Jiang, Yingxin Li, Sujun Zhao, Zhixi Yun, Zuo-Han Zhao, Lingli Zhang, Gaoyu Wang, Xin Chen, Linus Manubens-Gil, Yuning Hang, Qiaobo Gong, Yuanyuan Li, Penghao Qian, Lei Qu, Marta Garcia-Forn, Wei Wang, Silvia De Rubeis, Zhuhao Wu, Pavel Osten, Hui Gong, Michael Hawrylycz, Partha Mitra, Hongwei Dong, Qingming Luo, Giorgio A. Ascoli, Hongkui Zeng, Lijuan Liu, Hanchuan Peng
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引用次数: 0

Abstract

We conducted a large-scale whole-brain morphometry study by analyzing 3.7 peta-voxels of mouse brain images at the single-cell resolution, producing one of the largest multi-morphometry databases of mammalian brains to date. We registered 204 mouse brains of three major imaging modalities to the Allen Common Coordinate Framework (CCF) atlas, annotated 182,497 neuronal cell bodies, modeled 15,441 dendritic microenvironments, characterized the full morphology of 1876 neurons along with their axonal motifs, and detected 2.63 million axonal varicosities that indicate potential synaptic sites. Our analyzed six levels of information related to neuronal populations, dendritic microenvironments, single-cell full morphology, dendritic and axonal arborization, axonal varicosities, and sub-neuronal structural motifs, along with a quantification of the diversity and stereotypy of patterns at each level. This integrative study provides key anatomical descriptions of neurons and their types across a multiple scales and features, contributing a substantial resource for understanding neuronal diversity in mammalian brains.

Abstract Image

通过全脑形态计量学研究多尺度的神经元多样性和刻板性
我们进行了一项大规模的全脑形态测量研究,以单细胞分辨率分析了 3.7 peta-voxels的小鼠大脑图像,建立了迄今为止最大的哺乳动物大脑多形态测量数据库之一。我们将三种主要成像模式的204个小鼠大脑登记到艾伦通用坐标框架(CCF)图谱中,注释了182497个神经元细胞体,建立了15441个树突微环境模型,描述了1876个神经元的完整形态及其轴突图案,并检测到263万个轴突变异点,这些变异点表示潜在的突触位点。我们分析了与神经元群、树突微环境、单细胞完整形态、树突和轴突轴化、轴突变异和次神经元结构图案相关的六个层次的信息,并对每个层次的图案的多样性和刻板性进行了量化。这项综合研究提供了神经元及其类型在多个尺度和特征上的关键解剖描述,为了解哺乳动物大脑神经元的多样性提供了大量资源。
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来源期刊
Nature Communications
Nature Communications Biological Science Disciplines-
CiteScore
24.90
自引率
2.40%
发文量
6928
审稿时长
3.7 months
期刊介绍: Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.
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