Modelling Perception with Artificial Neural Networks Book

List of contributors

Introduction: Modelling perception with artificial neural networks 1

Part I General themes 5

1 Neural networks for perceptual processing: from simulation tools to theories Kevin Gurney Gurney, Kevin 7

2 Sensory ecology and perceptual allocation: new prospects for neural networks Steven M. Phelps Phelps, Steven M. 35

Part II The use of artificial neural networks to elucidate the nature of perceptual processes in animals 61

3 Correlation versus gradient type motion detectors: the pros and cons Alexander Borst Borst, Alexander 63

4 Spatial constancy and the brain: insights from neural networks Lawrence H. Snyder Snyder, Lawrence H. 74

5 The interplay of Pavlovian and instrumental processes in devaluation experiments: a computational embodied neuroscience model tested with a simulated rat Gianluca Baldassarre Baldassarre, Gianluca 93

6 Evolution, (sequential) learning and generalisation in modular and nonmodular visual neural networks Raffaele Calabretta Calabretta, Raffaele 114

7 Effects of network structure on associative memory Tokashi Odagaki Odagaki, Tokashi 134

8 Neural networks and neuro-oncology: the complex interplay between brain tumour, epilepsy and cognition J. C. Reijneveld Reijneveld, J. C. 149

Part III Artificial neural networks as models of perceptual processing in ecology and evolutionary biology 185

9 Evolutionary diversification of mating behaviour: using artificial neural networks to study reproductive character displacement and speciation Michael J. Ryan Ryan, Michael J. 187

10 Applying artificial neural networks to the study of prey colouration Sami Merilaita Merilaita, Sami 215

11 Artificial neural networks in models of specialisation, guild evolution and sympatric speciation Wayne M. Getz Getz, Wayne M. 236

12 Probabilistic design principles for robust multi-modal communication networks Nihat Ay Ay, Nihat 255

13 Movement-based signalling and the physical world: modelling the changing perceptual task for receivers Richard A. Peters Peters, Richard A. 269

Part IV Methodological issues in the use of simple feedforward networks 293

14 How training and testing histories affect generalisation: a test of simple neural networks Magnus Enquist Enquist, Magnus 295

15 The need for stochastic replication of ecological neural networks Graeme D. Ruxton Ruxton, Graeme D. 308

16 Methodological issues in modelling ecological learning with neural networks Graeme D. Ruxton Ruxton, Graeme D. 318

17 Neural network evolution and artificial life research Colm O'Riordan O'Riordan, Colm 334

18 Current velocity shapes the functional connectivity of benthiscapes to stream insect movement Julian D. Olden Olden, Julian D. 351

19 A model biological neural network: the cephalopod vestibular system Abdul Chrachri Chrachri, Abdul 374

Index 390