Formation of neural networks with structural and functional features consistent with small-world network topology on surface-grafted polymer particles

Abstract

In vitroelectrophysiological investigation of neural activity at anetwork level holds tremendous potential for elucidatingunderlying features of brain function (and dysfunction). In standard neural network modelling systems, however, the fundamental three-dimensional (3D) character of the brain isa largely disregarded feature. This widely appliedneuroscientific strategy affects several aspects of the structure–function relationships of the resulting networks, alteringnetwork connectivity and topology, ultimately reducing thetranslatability of the results obtained. As these model systems increase in popularity, it becomes imperative that they capture,as accurately as possible, fundamental features of neuralnetworks in the brain, such as small-worldness. In this report,we combinein vitroneural cell culture with a biologicallycompatible scaffolding substrate, surface-grafted polymerparticles (PPs), to develop neural networks with 3D topology.Furthermore, we investigate their electrophysiological networkactivity through the use of 3D multielectrode arrays. Theresulting neural network activity shows emergent behaviour consistent with maturing neural networks capable of performing computations, i.e. activity patternssuggestive of both information segregation (desynchronized single spikes and local bursts)and information integration (network spikes). Importantly, we demonstrate that the resulting PP-structured neural networks show both structural and functional features consistent with small-worldnetwork topology.