creators_name: Spratling, Michael creators_name: Hayes, Gillian type: confpaper datestamp: 2000-11-15 lastmod: 2011-03-11 08:54:26 metadata_visibility: show title: A self-organising neural network for modelling cortical development ispublished: pub subjects: comp-sci-neural-nets full_text_status: public keywords: neural networks, self-organisation 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). date: 1998 date_type: published pagerange: 333-338 refereed: TRUE citation: Spratling, Michael and Hayes, Gillian (1998) A self-organising neural network for modelling cortical development. [Conference Paper] document_url: http://cogprints.org/1107/2/map_alg.ps