A01=Magnus Enquist
A01=Stefano Ghirlanda
Animal Behaviour (journal)
Animal cognition
Animal communication
Animal testing
Animal training
Artificial neural network
Author_Magnus Enquist
Author_Stefano Ghirlanda
Behavior
Behavior model
Behavioral ecology
Behavioral modeling
Behavioral neuroscience
Behaviorism
Biological neural network
Biological system
Category=RG
Cognitive model
Cognitive psychology
Cognitive science
Conceptualization (information science)
Control theory
Decision tree
Decision-making
Domestication
Electrical Synapses
eq_isMigrated=1
eq_nobargain
Ethology
Evolution
Evolution of nervous systems
Evolutionary dynamics
Evolutionary game theory
Explore Evolution
Expression (computer science)
Imprinting (psychology)
Instance (computer science)
Instruction set
Learning
Learning rule
Magnetic field
Mammal
Membrane potential
Mental representation
Model organism
Modes of reproduction
Motor control
Motor learning
Motor neuron
Motor system
Multilayer perceptron
Natural selection
Network model
Network theory
Neural development
Neural pathway
Neuroethology
Neuron
Neurophysiology
Neuroscience
Neurosecretion
Ontogeny
Processing (programming language)
Psychology
Regulation of gene expression
Sensory preconditioning
Sensory processing
Signal (electrical engineering)
Social evolution
Stimulus (physiology)
Stimulus control
Synapsis
Synaptic plasticity
The Computational Brain
Trait theory
Product details
- ISBN 9780691096339
- Weight: 397g
- Dimensions: 152 x 235mm
- Publication Date: 04 Sep 2005
- Publisher: Princeton University Press
- Publication City/Country: US
- Product Form: Paperback
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How can we make better sense of animal behavior by using what we know about the brain? This is the first book that attempts to answer this important question by applying neural network theory. Scientists create Artificial Neural Networks (ANNs) to make models of the brain. These networks mimic the architecture of a nervous system by connecting elementary neuron-like units into networks in which they stimulate or inhibit each other's activity in much the same way neurons do. This book shows how scientists can employ ANNs to analyze animal behavior, explore the general principles of the nervous systems, and test potential generalizations among species. The authors focus on simple neural networks to show how ANNs can be investigated by math and by computers. They demonstrate intuitive concepts that make the operation of neural networks more accessible to nonspecialists. The first chapter introduces various approaches to animal behavior and provides an informal introduction to neural networks, their history, and their potential advantages. The second chapter reviews artificial neural networks, including biological foundations, techniques, and applications.
The following three chapters apply neural networks to such topics as learning and development, classical instrumental condition, and the role of genes in building brain networks. The book concludes by comparing neural networks to other approaches. It will appeal to students of animal behavior in many disciplines. It will also interest neurobiologists, cognitive scientists, and those from other fields who wish to learn more about animal behavior.
Magnus Enquist is Professor of Ethology in the Department of Zoology at Stockholm University. Stefano Ghirlanda is Researcher of General Psychology in the Department of Psychology at the University of Bologna.
