|Author||: John T. Schmidt|
|Publisher||: Academic Press|
|Release Date||: 2019-10-15|
|ISBN 10||: 0128185805|
|Pages||: 472 pages|
Self-organizing Neural Maps: From Retina to Tectum describes the underlying processes that determine how retinal fibers self-organize into an orderly visual map. The formation of neural maps is a fundamental organizing concept in neurodevelopment that can shed light on developmental mechanisms and the functions of genes elsewhere. The book presents a summary of research in the retinotectal field with an ultimate goal of synthesizing how underlying mechanisms in neural development harmoniously come together to create life. A broad spectrum of neuroscientists and biomedical scientists with differing backgrounds and varied expertise will find this book useful. Describes the mechanisms relating to the developmental wiring of the retinotectal system Brings together the state-of-the-art research in axon guidance and neuronal activity mechanisms in map formation Focuses on topographical maps and inclusion of multiple animal models, from fish to mammals Explores the molecular guidance and activity dependent cue components involved in neurodevelopment
An important collection showing how computational and mathematical modeling can beused to study the complexities of neural development.
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
|Author||: M.A. Corner,F.H. Lopes da Silva,H.B.M. Uylings,J. van Pelt|
|Release Date||: 1994-10-11|
|ISBN 10||: 0080862276|
|Pages||: 443 pages|
This book concentrates on the organizational level of neurons and neuronal networks under the unifying theme "The Self-Organizing Brain - From Growth Cones to Functional Networks". Such a theme is attractive because it incorporates all phases in the emergence of complexity and (adaptive) organization, as well as involving processes that remain operative in the mature state. The order of the sections follows successive levels of organization from neuronal growth cones, neurite formation, neuronal morphology and signal processing to network development, network dynamics and, finally, to the formation of functional circuits.
|Release Date||: 1988|
|Pages||: 329 pages|
This comprehensive bibliography provides a functional, flexible tool for researchers and engineers in neurocomputing.
One of the most challenging and fascinating problems of the theory of neural nets is that of asymptotic behavior, of how a system behaves as time proceeds. This is of particular relevance to many practical applications. Here we focus on association, generalization, and representation. We turn to the last topic first. The introductory chapter, "Global Analysis of Recurrent Neural Net works," by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding. It includes a review of the recent work with John Hopfield on integrate-and fire neurons with local interactions. The chapter, "Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns" by Ken Miller, explains how the primary visual cortex may asymptotically gain its specific structure through a self-organization process based on Hebbian learning. His argu ment since has been shown to be rather susceptible to generalization.
The human brain, wi th its hundred billion or more neurons, is both one of the most complex systems known to man and one of the most important. The last decade has seen an explosion of experimental research on the brain, but little theory of neural networks beyond the study of electrical properties of membranes and small neural circuits. Nonetheless, a number of workers in Japan, the United States and elsewhere have begun to contribute to a theory which provides techniques of mathematical analysis and computer simulation to explore properties of neural systems containing immense numbers of neurons. Recently, it has been gradually recognized that rather independent studies of the dynamics of pattern recognition, pattern format::ion, motor control, self-organization, etc. , in neural systems do in fact make use of common methods. We find that a "competition and cooperation" type of interaction plays a fundamental role in parallel information processing in the brain. The present volume brings together 23 papers presented at a U. S. -Japan Joint Seminar on "Competition and Cooperation in Neural Nets" which was designed to catalyze better integration of theory and experiment in these areas. It was held in Kyoto, Japan, February 15-19, 1982, under the joint sponsorship of the U. S. National Science Foundation and the Japan Society for the Promotion of Science. Participants included brain theorists, neurophysiologists, mathematicians, computer scientists, and physicists. There are seven papers from the U. S.
|Author||: Michael A. Arbib,Ronald L. Numbers,Fletcher Jones Professor of Computer Science and Professor of Biological Sciences Biomedical Engineering Neuroscience and Psychology Michael A Arbib,Peter Erdi,Péter Érdi,János Szentágothai,Janos Szentagothai,Alice Szentagothai|
|Publisher||: MIT Press|
|Release Date||: 1998|
|ISBN 10||: 9780262011594|
|Pages||: 407 pages|
In Neural Organization, Arbib, Erdi, and Szentagothai integrate structural, functional, and dynamical approaches to the interaction of brain models and neurobiologcal experiments. Both structure-based "bottom-up" and function- based "top-down" models offer coherent concepts by which to evaluate the experimental data. The goal of this book is to point out the advantages of a multidisciplinary, multistrategied approach to the brain.Part I of Neural Organization provides a detailed introduction to each of the three areas of structure, function, and dynamics. Structure refers to the anatomical aspects of the brain and the relations between different brain regions. Function refers to skills and behaviors, which are explained by means of functional schemas and biologically based neural networks. Dynamics refers to the use of a mathematical framework to analyze the temporal change of neural activities and synaptic connectivities that underlie brain development and plasticity--in terms of both detailed single-cell models and large-scale network models.In part II, the authors show how their systematic approach can be used to analyze specific parts of the nervous system--the olfactory system, hippocampus, thalamus, cerebral cortex, cerebellum, and basal ganglia--as well as to integrate data from the study of brain regions, functional models, and the dynamics of neural networks. In conclusion, they offer a plan for the use of their methods in the development of cognitive neuroscience."
This presentation of the foremost research and theory from disciplines that provide the foundations of neural network research--neurobiology, physics, computer science, electrical engineering, mathematics, and psychology--shows how neural networks and neurocomputing represent radical departures from conventional approaches to digital computers, in terms of algorithms and architecture.
Vols. for 1942- include proceedings of the American Physiological Society.
Publishes original critical reviews of the significant literature and current developments in psychology.
A new perspective on topographic map formation and the advantages of information-based learning The study of topographic map formation provides us with important tools for both biological modeling and statistical data modeling. Faithful Representations and Topographic Maps offers a unified, systematic survey of this rapidly evolving field, focusing on current knowledge and available techniques for topographic map formation. The author presents a cutting-edge, information-based learning strategy for developing equiprobabilistic topographic maps--that is, maps in which all neurons have an equal probability to be active--clearly demonstrating how this approach yields faithful representations and how it can be successfully applied in such areas as density estimation, regression, clustering, and feature extraction. The book begins with the standard approach of distortion-based learning, discussing the commonly used Self-Organizing Map (SOM) algorithm and other algorithms, and pointing out their inadequacy for developing equiprobabilistic maps. It then examines the advantages of information-based learning techniques, and finally introduces a new algorithm for equiprobabilistic topographic map formation using neurons with kernel-based response characteristics. The complete learning algorithms and simulation details are given throughout, along with comparative performance analysis tables and extensive references. Faithful Representations and Topographic Maps is an excellent, eye-opening guide for neural network researchers, industrial scientists involved in data mining, and anyone interested in self-organization and topographic maps.
|Author||: Edward L. Keller,David S. Zee|
|Release Date||: 1986|
|Pages||: 496 pages|