  The organization of the connectivity between mammalian cortical areas has
become a major subject of study, because of its important role in scaffolding
the macroscopic aspects of animal behavior and intelligence. In this study we
present a computational reconstruction approach to the problem of network
organization, by considering the topological and spatial features of each area
in the primate cerebral cortex as subsidy for the reconstruction of the global
cortical network connectivity. Starting with all areas being disconnected,
pairs of areas with similar sets of features are linked together, in an attempt
to recover the original network structure. Inferring primate cortical
connectivity from the properties of the nodes, remarkably good reconstructions
of the global network organization could be obtained, with the topological
features allowing slightly superior accuracy to the spatial ones. Analogous
reconstruction attempts for the C. elegans neuronal network resulted in
substantially poorer recovery, indicating that cortical area interconnections
are relatively stronger related to the considered topological and spatial
properties than neuronal projections in the nematode. The close relationship
between area-based features and global connectivity may hint on developmental
rules and constraints for cortical networks. Particularly, differences between
the predictions from topological and spatial properties, together with the
poorer recovery resulting from spatial properties, indicate that the
organization of cortical networks is not entirely determined by spatial
constraints.
