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用于狨猴大脑皮质内连接的细胞分辨率分析的开放获取资源。

Open access resource for cellular-resolution analyses of corticocortical connectivity in the marmoset monkey.

机构信息

Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 3 Pasteur Street, 02-093, Warsaw, Poland.

Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, 3800, Australia.

出版信息

Nat Commun. 2020 Feb 28;11(1):1133. doi: 10.1038/s41467-020-14858-0.

Abstract

Understanding the principles of neuronal connectivity requires tools for efficient quantification and visualization of large datasets. The primate cortex is particularly challenging due to its complex mosaic of areas, which in many cases lack clear boundaries. Here, we introduce a resource that allows exploration of results of 143 retrograde tracer injections in the marmoset neocortex. Data obtained in different animals are registered to a common stereotaxic space using an algorithm guided by expert delineation of histological borders, allowing accurate assignment of connections to areas despite interindividual variability. The resource incorporates tools for analyses relative to cytoarchitectural areas, including statistical properties such as the fraction of labeled neurons and the percentage of supragranular neurons. It also provides purely spatial (parcellation-free) data, based on the stereotaxic coordinates of 2 million labeled neurons. This resource helps bridge the gap between high-density cellular connectivity studies in rodents and imaging-based analyses of human brains.

摘要

理解神经元连接的原理需要高效量化和可视化大型数据集的工具。灵长类动物皮层尤其具有挑战性,因为它的区域存在复杂的镶嵌,在许多情况下缺乏明确的边界。在这里,我们介绍了一个资源,允许探索 143 个逆行示踪剂注射在狨猴新皮层中的结果。使用专家划定组织学边界指导的算法,将在不同动物中获得的数据注册到共同的立体空间中,允许在个体间变异性的情况下准确地将连接分配到区域。该资源包含了针对细胞构筑区域的分析工具,包括标记神经元的分数和颗粒上层神经元的百分比等统计属性。它还提供了基于 200 万个标记神经元的立体坐标的纯空间(无分割)数据。这个资源有助于弥合在啮齿动物中进行高密度细胞连接研究和基于成像的人类大脑分析之间的差距。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da0d/7048793/f2d044651c2f/41467_2020_14858_Fig1_HTML.jpg

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