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《通过超密集皮质图特征化的鼠大脑皮质连接组,通过独特的连接模式保持特异性》

The Mouse Cortical Connectome, Characterized by an Ultra-Dense Cortical Graph, Maintains Specificity by Distinct Connectivity Profiles.

机构信息

Université Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, 69500 Bron, France.

Université Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, 69500 Bron, France; Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS) Key Laboratory of Primate Neurobiology, CAS, Shanghai 200031, China.

出版信息

Neuron. 2018 Feb 7;97(3):698-715.e10. doi: 10.1016/j.neuron.2017.12.037.

DOI:10.1016/j.neuron.2017.12.037
PMID:29420935
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5958229/
Abstract

The inter-areal wiring pattern of the mouse cerebral cortex was analyzed in relation to a refined parcellation of cortical areas. Twenty-seven retrograde tracer injections were made in 19 areas of a 47-area parcellation of the mouse neocortex. Flat mounts of the cortex and multiple histological markers enabled detailed counts of labeled neurons in individual areas. The observed log-normal distribution of connection weights to each cortical area spans 5 orders of magnitude and reveals a distinct connectivity profile for each area, analogous to that observed in macaques. The cortical network has a density of 97%, considerably higher than the 66% density reported in macaques. A weighted graph analysis reveals a similar global efficiency but weaker spatial clustering compared with that reported in macaques. The consistency, precision of the connectivity profile, density, and weighted graph analysis of the present data differ significantly from those obtained in earlier studies in the mouse.

摘要

分析了与皮层区域细分相关的小鼠大脑皮层的区域间布线模式。在小鼠新皮层的 47 个分区的 19 个分区中进行了 27 次逆行示踪剂注射。皮质的平片和多种组织学标记物使我们能够对每个区域中的标记神经元进行详细计数。观察到的连接权重的对数正态分布跨越 5 个数量级,为每个区域揭示了独特的连接模式,类似于在猕猴中观察到的模式。皮质网络的密度为 97%,明显高于猕猴报告的 66%密度。加权图分析显示,与猕猴相比,全局效率相似,但空间聚类较弱。与之前在小鼠中进行的研究相比,本研究中数据的连接模式的一致性、精度、密度和加权图分析有显著差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/82e47ef3746d/nihms931062f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/f0ad21fb988c/nihms931062f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/d8411c1d987f/nihms931062f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/e155cff895b6/nihms931062f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/c2dc9ad36465/nihms931062f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/1787287a815d/nihms931062f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/82e47ef3746d/nihms931062f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/f0ad21fb988c/nihms931062f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/e0bb9498d9a7/nihms931062f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/2923e1a6c88a/nihms931062f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/d8411c1d987f/nihms931062f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/e155cff895b6/nihms931062f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/c2dc9ad36465/nihms931062f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/1787287a815d/nihms931062f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19cd/5958229/82e47ef3746d/nihms931062f8.jpg

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