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猴脑皮质的加权有向区域间连接矩阵。

A weighted and directed interareal connectivity matrix for macaque cerebral cortex.

机构信息

Stem cell and Brain Research Institute, INSERM U846, 69500 Bron, France.

出版信息

Cereb Cortex. 2014 Jan;24(1):17-36. doi: 10.1093/cercor/bhs270. Epub 2012 Sep 25.

Abstract

Retrograde tracer injections in 29 of the 91 areas of the macaque cerebral cortex revealed 1,615 interareal pathways, a third of which have not previously been reported. A weight index (extrinsic fraction of labeled neurons [FLNe]) was determined for each area-to-area pathway. Newly found projections were weaker on average compared with the known projections; nevertheless, the 2 sets of pathways had extensively overlapping weight distributions. Repeat injections across individuals revealed modest FLNe variability given the range of FLNe values (standard deviation <1 log unit, range 5 log units). The connectivity profile for each area conformed to a lognormal distribution, where a majority of projections are moderate or weak in strength. In the G29 × 29 interareal subgraph, two-thirds of the connections that can exist do exist. Analysis of the smallest set of areas that collects links from all 91 nodes of the G29 × 91 subgraph (dominating set analysis) confirms the dense (66%) structure of the cortical matrix. The G29 × 29 subgraph suggests an unexpectedly high incidence of unidirectional links. The directed and weighted G29 × 91 connectivity matrix for the macaque will be valuable for comparison with connectivity analyses in other species, including humans. It will also inform future modeling studies that explore the regularities of cortical networks.

摘要

在食蟹猴大脑皮层的 91 个区域中的 29 个区域进行逆行示踪剂注射,揭示了 1615 条区域间通路,其中三分之一以前尚未报道过。为每条区域间通路确定了权重指数(标记神经元的外在分数 [FLNe])。与已知的投射相比,新发现的投射平均较弱;然而,这两组通路的权重分布广泛重叠。在个体之间进行重复注射显示,FLNe 值的范围(标准偏差 <1 对数单位,范围 5 对数单位)给出了适度的 FLNe 可变性。每个区域的连接谱符合对数正态分布,其中大多数投射的强度为中等或较弱。在 G29×29 区域间子图中,存在的连接中有三分之二存在。对从 G29×91 子图的所有 91 个节点收集链接的最小区域集(主导集分析)的分析证实了皮质矩阵的密集(66%)结构。G29×29 子图表明单向链接的发生率出乎意料地高。食蟹猴的有向加权 G29×91 连通性矩阵将有助于与其他物种(包括人类)的连通性分析进行比较。它还将为探索皮质网络规律的未来建模研究提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d37/3862262/3e0c6bae8510/bhs27001.jpg

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