Book contents
- Frontmatter
- Contents
- Contributors
- Introduction: Modelling perception with artificial neural networks
- Part I General themes
- 1 Neural networks for perceptual processing: from simulation tools to theories
- 2 Sensory ecology and perceptual allocation: new prospects for neural networks
- Part II The use of artificial neural networks to elucidate the nature of perceptual processes in animals
- Part III Artificial neural networks as models of perceptual processing in ecology and evolutionary biology
- Part IV Methodological issues in the use of simple feedforward networks
- Index
- References
2 - Sensory ecology and perceptual allocation: new prospects for neural networks
from Part I - General themes
Published online by Cambridge University Press: 05 July 2011
- Frontmatter
- Contents
- Contributors
- Introduction: Modelling perception with artificial neural networks
- Part I General themes
- 1 Neural networks for perceptual processing: from simulation tools to theories
- 2 Sensory ecology and perceptual allocation: new prospects for neural networks
- Part II The use of artificial neural networks to elucidate the nature of perceptual processes in animals
- Part III Artificial neural networks as models of perceptual processing in ecology and evolutionary biology
- Part IV Methodological issues in the use of simple feedforward networks
- Index
- References
Summary
Introduction
All of animal behaviour can be considered a series of choices – at any given moment an animal must decide whether to mate, eat, sleep, fight or simply rest. Such decisions require estimates of the immediate environment, and despite the diversity of those estimates, they are all carried out by sensory systems and the neural functions contingent on them. This functional diversity is central to the concept of sensory drive (Endler, 1992; Figure 2.1), which notes that animal mating, foraging and other activities are evolutionarily coupled through their shared dependence on sensory systems and local environments. In light of the many demands made of a sensory system, what does it mean to design one well?
It is often useful to consider how an ideal receiver would perform on a given task. Aside from the potentially conflicting demands posed by different aspects of one's environment, there are additional reasons to think that such an approach may not be complete. The climb to a global optimum can be a tortuous one, complicated by genetic drift, allelic diversity and phylogenetic history. Analytic models often focus on defining the best possible performance and neglect the existence of alternative local optima, or the ability to arrive at such optima through evolutionary processes. In sexual selection, researchers have suggested pleiotropy in sensory systems may be one key feature that shapes the direction of evolution (Kirkpatrick & Ryan, 1991).
- Type
- Chapter
- Information
- Modelling Perception with Artificial Neural Networks , pp. 35 - 60Publisher: Cambridge University PressPrint publication year: 2010