Brain inspired cognitive systems (BICS)

Abstract

This Neurocomputing special issue is based on selected, expanded and significantly revised versions of papers presented at the Second International Conference on Brain Inspired Cognitive Systems (BICS 2006) held at Lesvos, Greece, from 10 to 14 October 2006. The aim of BICS 2006, which followed the very successful first BICS 2004 held at Stirling, Scotland, was to bring together leading scientists and engineers who use analytic, syntactic and computational methods both to understand the prodigious processing properties of biological systems and, specifically, of the brain, and to exploit such knowledge to advance computational methods towards ever higher levels of cognitive competence. The biennial BICS Conference Series (with BICS 2008 recently held in Sao Luis, Brazil, 24–27 June, and BICS 2010 due to be held in Madrid, Spain) aims to become a major point of contact for research scientists, engineers and practitioners throughout the world in the fields of cognitive and computational systems inspired by the brain and biology. The first paper in this special issue is by Carnell who presents an analysis of the use of Hebbian and Anti-Hebbian spike timedependent plasticity (STDP) learning functions within the context of recurrent spiking neural networks. He shows that under specific conditions Hebbian and Anti-Hebbian learning can be considered approximately equivalent. Finally, the author demonstrates that such a network habituates to a given stimulus and is capable of detecting subtle variations in the structure of the stimuli itself. Hodge, O’Keefe and Austin present a binary neural shape matcher using Johnson counters and chain codes. They show that images may be matched as whole images or using shape matching. Finally, they demonstrate shape matching using a binary associative-memory neural network to index and match chain codes where the chain code elements are represented by Johnson codes.

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Ron Chrisley
University of Sussex

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