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A presentation of all aspects of neural crest cell origins (embryological and evolutionary) development and evolution; neural crest cell behavior (migration) and anomalies (neurocristopathies and birth defects) that arise from defective neural crest development. The treatment of development will include discussions of cellular, molecular and genetic aspects of the differentiation and morphogenesis of neural crest cells and structures derived from neural crest cells. The origins of the neural crest in embryology will be discussed using the recent information on the molecular basis of the specification of the neural crest. Also presented are the advances in our understanding of the evolution of jaws from studies on lampreys and of the neural crest from studies on ascidians and amphioxus.

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Neural Networks in C++ An Object-Oriented Framework for Building Connectionist Systems Extremely useful, this valuable guide concentrates on the practical side of building neural network applications. Written with a wealth of useful examples in C++, the book provides you with the nuts-and-bolts guidelines for hands-on development of real-world connectionist systems. Neural Networks in C++ also: Includes a complete C++ class library especially designed for neural network applications Fully covers three major application areas of neural network programming—image recognition, text processing, and forecasting Provides introductory material on neural networks Covers the basics on an object-oriented framework for connectionist systems

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Winner, 2011 Alpha Sigma Nu Book Award in Literature and Fine ArtsThe Neural Sublime brings recent work in cognitive neuroscience to bear on some famously vexed issues in British Romantic studies. In exciting and unprecedented ways, Alan Richardson demonstrates how developments in the neurosciences can transform the study of literary history. Richardson presents six exemplary studies, each exploring a different intersection of Romanticism and the sciences of the mind and brain: the experience of the sublime and the neuroscience of illusion; the Romantic imagination and visual imaging; the figure of apostrophe and linguistic theory; fictional representations of the mind and "theory of mind" theory; depictions of sibling incest and neo-Darwinian theories of mental behavior; and representations of female speech and cognitive developmental psychology. Richardson’s insightful analysis opens fresh perspectives on British Romanticism, pointing scholars to new developments in cognitive literary studies. He combines elements of new historicist analysis with original―and much-needed―models for understanding language, subjectivity, and social behavior. Far from signaling a departure from the prevalent critical approaches of new historicism, Richardson argues, cognitive theory presents an essential complement to them.The Neural Sublime features an array of cognitive and neuroscientific approaches, providing an engaging and readable introduction to the emergent field of cognitive literary studies.

Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.

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This fully revised edition of The Neural Crest contains the most current information about this unique structure that has a transient existence in early embryonic life. The ontogeny of the neural crest embodies the most important issues in developmental biology, as the neural crest is considered to have played a crucial role in evolution of the vertebrate phylum. This revised edition includes new data that analyze neural crest ontogeny in murine and zebrafish embryos. Additional features include coverage of advances in our understanding of neural crest cell subpopulation markers, cell lineage analysis, and the introduction of molecular biology to neural crest research. Like its predecessor, this volume is essential reading for students and researchers in developmental biology, cell biology, and neuroscience.

Reviews and discussions of contemporary and relevant topics by leading investigators, essential for all those wishing to take advantage of the latest and greatest in this emerging field.

Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

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Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.

Using an engineering and science perspective, it explores diverse neural network, fuzzy logic and genetic algorithm techniques plus developing applications best suited for each of the methods discussed. Sample results are described and judgment made as to how well each application worked. The book/disk set includes an object-oriented user interface along with the code for numerous programs.

For years, researchers have used the theoretical tools of engineering to understand neural systems, but much of this work has been conducted in relative isolation. In Neural Engineering, Chris Eliasmith and Charles Anderson provide a synthesis of the disparate approaches current in computational neuroscience, incorporating ideas from neural coding, neural computation, physiology, communications theory, control theory, dynamics, and probability theory. This synthesis, they argue, enables novel theoretical and practical insights into the functioning of neural systems. Such insights are pertinent to experimental and computational neuroscientists and to engineers, physicists, and computer scientists interested in how their quantitative tools relate to the brain. The authors present three principles of neural engineering based on the representation of signals by neural ensembles, transformations of these representations through neuronal coupling weights, and the integration of control theory and neural dynamics. Through detailed examples and in-depth discussion, they make the case that these guiding principles constitute a useful theory for generating large-scale models of neurobiological function. A software package written in MatLab for use with their methodology, as well as examples, course notes, exercises, documentation, and other material, are available on the Web.

Winner, 2011 Alpha Sigma Nu Book Award in Literature and Fine ArtsThe Neural Sublime brings recent work in cognitive neuroscience to bear on some famously vexed issues in British Romantic studies. In exciting and unprecedented ways, Alan Richardson demonstrates how developments in the neurosciences can transform the study of literary history. Richardson presents six exemplary studies, each exploring a different intersection of Romanticism and the sciences of the mind and brain: the experience of the sublime and the neuroscience of illusion; the Romantic imagination and visual imaging; the figure of apostrophe and linguistic theory; fictional representations of the mind and "theory of mind" theory; depictions of sibling incest and neo-Darwinian theories of mental behavior; and representations of female speech and cognitive developmental psychology. Richardson’s insightful analysis opens fresh perspectives on British Romanticism, pointing scholars to new developments in cognitive literary studies. He combines elements of new historicist analysis with original―and much-needed―models for understanding language, subjectivity, and social behavior. Far from signaling a departure from the prevalent critical approaches of new historicism, Richardson argues, cognitive theory presents an essential complement to them.The Neural Sublime features an array of cognitive and neuroscientific approaches, providing an engaging and readable introduction to the emergent field of cognitive literary studies.

Zustand: Hervorragend Seiten: 174 Sprache: Englisch Produktart: Bücher