Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat

The number of different cortical structures in mammalian brains and the num ber of extrinsic fibres linking these regions are both large. As with any c omplex system, systematic analysis is required to draw reliable conclusions about the organization of the complex neural networks comprising these num erous elements. One aspect of organization that has long been suspected is that cortical networks are organized into 'streams' or 'systems'. Here we r eport computational analyses capable of showing whether clusters of strongl y interconnected areas are aspects of the global organization of cortical s ystems in macaque and cat. We used two different approaches to analyse comp ilations of corticocortical connection data from the macaque and the cat. T he first approach, optimal set analysis, employed an explicit definition of a neural 'system' or 'stream', which was based on differential connectivit y We defined a two-component cost function that described the cost of the g lobal cluster arrangement of areas in terms of the areas' connectivity with in and between candidate clusters. Optimal cluster arrangements of cortical areas were then selected computationally from the very many possible arran gements, using an evolutionary optimization algorithm. The second approach, non-parametric cluster analysis (NPCA), grouped cortical areas on the basi s of their proximity in multidimensional scaling representations. We used n on-metric multidimensional scaling to represent the cortical connectivity s tructures metrically in two and five dimensions. NPCA then analysed these r epresentations to determine the nature of the clusters for a wide range of different cluster shape parameters. The results from both approaches largely agreed. They showed chat macaque a nd cat cortices are organized into densely intra-connected clusters of area s, and identified the constituent members of the clusters. These clusters r eflected functionally specialized sets of cortical areas, suggesting that s tructure and function are closely linked at this gross, systems level.