A self-organising neural network for modelling cortical development

Abstract

This paper presents a novel self-organising neural network. It has been developed for use as a simplified model of cortical development. Unlike many other models of topological map formation all synaptic weights start at zero strength (so that synaptogenesis might be modelled). In addition, the algorithm works with the same format of encoding for both inputs to and outputs from the network (so that the transfer and recoding of information between cortical regions might be modelled).