Introduction: Modelling perception with artificial neural networks

This book represents a substantial update of a theme issue of the Philosophical Transactions of the Royal Society B Journal, ‘The use of artificial neural networks to study perception in animals’ (Phil Trans R Soc B 2007 March 29; 362(1479)). Most of the 14 papers in that theme issue have been significantly updated and we include a further five entirely new chapters, reflecting emerging themes in neural network research. Our reasons for undertaking the theme issue and this book were not entirely altruistic. Having a young but growing interest in the use of artificial neural networks, we hoped that the publications would be an excuse for us to learn about areas in neural network research that seemed interesting to us and of potential application to our research. The people who will get most from the book are, therefore, ecologists and evolutionary biologists, perhaps with a notion of using neural network models of perception, but with little experience of their use. That said, the content of this book is extremely broad and we are confident that there is something in it for any scientist with an interest in animal (including human) perception and behaviour. We organise the book into four fairly loose categories. The chapters by Kevin Gurney and Steve Phelps are broad reviews and introduce the two main themes of the book: neural networks as tools to explore the nature of perceptual processes, and neural networks as models of perception in ecology and evolutionary biology. Kevin Gurney’s chapter is an excellent general introduction to the theory and use of neural networks and tackles the question: what can simple neural network models tell us about real neural circuits and the brain? Steve Phelps’s chapter is a ‘where it’s at and where it’s going’ of artificial neural network models used to explore perceptual allocation and bias, and the models and ideas in it can be applied to many other areas of ecology and evolutionary biology. Like most of the articles in the book, both of these chapters can be appreciated by those with little or no mathematical expertise. The next six chapters are research or focused review articles on neural network models and their use in elucidating the nature of perceptual processes in animals. Axel Borst’s chapter describes and compares the properties of different neural models of motion