Scannell J W, Blakemore C, Young M P
University Laboratory of Physiology, Oxford, United Kingdom.
J Neurosci. 1995 Feb;15(2):1463-83. doi: 10.1523/JNEUROSCI.15-02-01463.1995.
The mammalian cerebral cortex is innervated by a large number of corticocortical connections. The number of connections makes it difficult to understand the organization of the cortical network. Nonetheless, conclusions about the organization of cortical systems drawn from examining connectional data have often been made in a speculative and informal manner, unsupported by any analytic treatment. Recently, progress has been made toward more systematic ways of extracting organizing principles from data on the network of connections between cortical areas of the monkey. In this article, we extend these approaches to the cortical systems of the cat. We collated information from the neuroanatomical literature about the corticocortical connections of the cat. This collation incorporated 1139 reported corticocortical connections between 65 cortical areas. We have previously used an optimization technique (Scannell and Young, 1993) to analyze this database in order to represent the connectional organization of cortical systems in the cat. Here, we report the connectional database and analyze it in a number of further ways. First, we employed rules from Felleman and Van Essen (1991) to investigate hierarchical relations among the areas. Second, we compared quantitatively the results of the optimization method with the results of the hierarchical method. Third, we examined quantitatively whether simple connection rules, which may reflect the development and evolution of the cortex, can account for the experimentally identified corticocortical connections in the database. The results showed, first, that hierarchical rules, when applied to the cat visual system, define a largely consistent hierarchy. Second, in both auditory and visual systems, the ordering of areas by hierarchical analysis and by optimization analysis was statistically significantly related. Hence, independent analyzes concur broadly in their ordering of areas in the cortical hierarchies. Third, the majority of corticocortical connections, and much of the pattern of connectivity, were accounted for by a simple "nearest-neighbor-or-next-door-but-one" connection rule, which may suggest one of the mechanisms by which the development of cortical connectivity is controlled.
哺乳动物的大脑皮层由大量的皮质-皮质连接所支配。连接数量众多，使得理解皮质网络的组织变得困难。尽管如此，从检查连接数据得出的关于皮质系统组织的结论，往往是以一种推测性和非正式的方式得出的，缺乏任何分析处理的支持。最近，在从猴子皮质区域之间的连接网络数据中提取组织原则的更系统方法方面取得了进展。在本文中，我们将这些方法扩展到猫的皮质系统。我们整理了神经解剖学文献中关于猫的皮质-皮质连接的信息。这次整理纳入了65个皮质区域之间报告的1139个皮质-皮质连接。我们之前使用一种优化技术（斯坎内尔和杨，1993年）来分析这个数据库，以呈现猫皮质系统的连接组织。在这里，我们报告连接数据库并以多种进一步的方式对其进行分析。首先，我们采用费勒曼和范埃森（1991年）的规则来研究各区域之间的层级关系。其次，我们定量比较了优化方法的结果与层级方法的结果。第三，我们定量研究了可能反映皮质发育和进化的简单连接规则，是否能够解释数据库中实验确定的皮质-皮质连接。结果表明，首先，当将层级规则应用于猫的视觉系统时，定义了一个基本一致的层级结构。其次，在听觉和视觉系统中，通过层级分析和优化分析对区域的排序在统计学上显著相关。因此，独立分析在皮质层级中对区域的排序上大致一致。第三，大多数皮质-皮质连接以及许多连接模式，可以由一个简单的“最近邻或隔一个邻居”连接规则来解释，这可能暗示了控制皮质连接发育的机制之一。
