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The Journal of Neuroscience logoLink to The Journal of Neuroscience
. 1995 Feb 1;15(2):1463–1483. doi: 10.1523/JNEUROSCI.15-02-01463.1995

Analysis of connectivity in the cat cerebral cortex

JW Scannell 1, C Blakemore 1, MP Young 1
PMCID: PMC6577853  PMID: 7869111

Abstract

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.


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