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This volume constitutes the proceedings of the 7th International Conference on Simulated Evolution and Learning, SEAL 2008, held in Melbourne, Australia, during December 7-10, 2008. The 65 papers presented were carefully reviewed and selected from 140 submissions. The topics covered are evolutionary learning; evolutionary optimisation; hybrid learning; adaptive systems; theoretical issues in evolutionary computation; and real-world applications of evolutionary computation techniques.
The fruitfly Drosophila melanogaster is an ideal model system to study processes of the central nervous system This book provides an overview of some major facets of recent research on Drosophila brain development.
This is a new edition in the Cellular and Molecular Neurobiology series. The vast majority of cells in the nervous system are glial cells. During development, these cells provide growth factors that stimulate the proliferation, migration and survival of neurones and their precursors, andpromote and guide axonal growth. In the mature nervous system, glial cells provide insulating myelin sheathe around axons and provide metabolic and structural support for neurones. Glial cells also have a major influence on the local response to injury of the central nerve tract and the peripheralnervous system, either promoting, or inhibiting, axonal regrowth and recovery of lost function. This book provides a comprehensive, state-of-the-art overview of research into the development, function and malfunction of glial cells. It offers a compelling insight into how basic research throwslight onto diseases and disorders and points the way towards treatments. Teams of internationally renowned experts, all active in research, have contributed chapters.
The nervous system is highly complex both in its structural order and in its ability to perform the many functions required for survival and interaction with the environment; understanding how it develops has proven to be one of the greatest challenges in biology. Such precision demands that key events at every developmental stage are executed properly and are coordinated to produce the circuitry underlying each of the adult nervous system's functions. This volume describes the latest research on the cellular and molecular mechanisms of neural circuitry development, while providing researchers with a one-stop overview and synthesis of contemporary thought in the area. Reviews current research findings on the development of neural circuitry, providing researchers with an overview and synthesis of the latest contemporary thought in the cellular and molecular mechanisms that underlie the development of neural circuitry Includes chapters discussing topics such as the guidance of nerve growth and the formation of plasticity of synapses, helping researchers better understand underlying mechanisms of neural circuit development and maintenance that may play a role in such human diseases/conditions as depression, anxiety, and pain Chapters make use of a variety of human and animal models, allowing researchers to compare and contrast neural circuitry development across a wide spectrum of models
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.

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