Contents

pp v-vi

Contributors

pp vii-x

Introduction: Modelling perception with artificial neural networks

pp 1-4

Part I - General themes

pp 5-6

1 - Neural networks for perceptual processing: from simulation tools to theories

pp 7-34

2 - Sensory ecology and perceptual allocation: new prospects for neural networks

pp 35-60

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

pp 61-62

3 - Correlation versus gradient type motion detectors: the pros and cons

pp 63-73

4 - Spatial constancy and the brain: insights from neural networks

pp 74-92

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

pp 93-113

6 - Evolution, (sequential) learning and generalisation in modular and nonmodular visual neural networks

pp 114-133

7 - Effects of network structure on associative memory

pp 134-148

8 - Neural networks and neuro-oncology: the complex interplay between brain tumour, epilepsy and cognition

pp 149-184

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

pp 185-186

9 - Evolutionary diversification of mating behaviour: using artificial neural networks to study reproductive character displacement and speciation

pp 187-214

10 - Applying artificial neural networks to the study of prey colouration

pp 215-235

11 - Artificial neural networks in models of specialisation, guild evolution and sympatric speciation

pp 236-254

12 - Probabilistic design principles for robust multi-modal communication networks

pp 255-268

13 - Movement-based signalling and the physical world: modelling the changing perceptual task for receivers

pp 269-292

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

pp 293-294

14 - How training and testing histories affect generalisation: a test of simple neural networks

pp 295-307

15 - The need for stochastic replication of ecological neural networks

pp 308-317

16 - Methodological issues in modelling ecological learning with neural networks

pp 318-333

17 - Neural network evolution and artificial life research

pp 334-350

18 - Current velocity shapes the functional connectivity of benthiscapes to stream insect movement

pp 351-373

19 - A model biological neural network: the cephalopod vestibular system

pp 374-389

Index

pp 390-397