A Complex Network Approach to Topographical Connections

TL;DR

This paper uses complex network models to analyze how topographical connections in the mammalian cortex influence network properties like connectivity and information flow, revealing their role in enhancing intercellular communication.

Contribution

It introduces a novel application of complex network formalism to model and quantify the effects of topographical connections in cortical networks, comparing different intracortical connection models.

Findings

Topographical connections improve network connectivity and communication.

Different intracortical connection models affect network properties distinctly.

Spatially simple topographical links can significantly alter network dynamics.

Abstract

The neuronal networks in the mammals cortex are characterized by the coexistence of hierarchy, modularity, short and long range interactions, spatial correlations, and topographical connections. Particularly interesting, the latter type of organization implies special demands on the evolutionary and ontogenetic systems in order to achieve precise maps preserving spatial adjacencies, even at the expense of isometry. Although object of intensive biological research, the elucidation of the main anatomic-functional purposes of the ubiquitous topographical connections in the mammals brain remains an elusive issue. The present work reports on how recent results from complex network formalism can be used to quantify and model the effect of topographical connections between neuronal cells over a number of relevant network properties such as connectivity, adjacency, and information broadcasting. While the topographical mapping between two cortical modules are achieved by connecting nearest cells from each module, three kinds of network models are adopted for implementing intracortical connections (ICC), including random, preferential-attachment, and short-range networks. It is shown that, though spatially uniform and simple, topographical connections between modules can lead to major changes in the network properties, fostering more effective intercommunication between the involved neuronal cells and modules. The possible implications of such effects on cortical operation are discussed.