الصفحة 7
الصفحة 7
Neurodegeneration in Multiple Sclerosis
In multiple sclerosis (MS), conventional magnetic resonance imaging (cMRI) has proved to be a valuable tool to increase diagnostic reliability and to monitor the efficacy of experimental treatment. However, cMRI has limited specificity and accuracy as to the most disabling aspects of the MS pathology, known to occur in and outside macroscopic lesions. Modern quantitative MR techniques have the potential to overcome the limitations of cMRI, and their application is dramatically changing our understanding of how MS causes irreversible disability.
Neurocutaneous Disorders : Phakomatoses and Hamartoneoplastic Syndromes
Neurocutaneous diseases are a wide group of conditions that affect the nervous system but appear as lesions of the skin. Some of the more common entities have variable forms of expression that can confuse the diagnosis; for the rare conditions it is difficult to find descriptions in the literature. Recent insights into their cellular, biochemical and molecular genetic bases have shown the essential need for a new nosology and updated genotype-phenotype correlations. The book provides an authoritative source of knowledge about these difficult problems and bridges the gap between clinical recognition and the new molecular medicine. The editors, distinguished clinicians and geneticists, assembled an internationally renowned group of collaborators, many of them the experts who first described a particular disorder or established its present accepted definition.
Neurocutaneous disorders : A clinical, ciagnostic and therapeutic approach
Provides extensive data on the more common and many of the more rare congenital and hereditary syndromes that manifest in the nervous system and skin. Though often complex and multi-systemic, these disorders can frequently be diagnosed using a combination of simple visual inspection and sound clinical expertise. Drawing on fully referenced information from thousands of articles, the international editorial team has prepared a comprehensive overview that includes historical perspectives, clinical features, the pathogenesis, and diagnostic and therapeutic strategies. In addition, it addresses the biochemical, molecular, and genetic basis of the disorders.
Neuroblastoma
Neuroblastoma is a medical enigma. As a childhood neoplasm arising from neural crest cells, it is characterized by diverse clinical behaviors ranging from spontaneous remission to rapid tumor progression and death. Although clinical outcome can be predicted to a large extent by the stage of disease and the age at diagnosis, an in-depth understanding of its clinico-pathological behavior, now greatly aided by sophisticated molecular genetic profiling, will improve diagnostic precision and refine risk-based therapies. Comprehensive international efforts have advanced our understanding of tumor biology and improved the clinical management of children with neuroblastoma. This book reviews our current understanding of the genes and biological pathways that contribute to neuroblastoma pathogenesis, modern risk-based treatment approaches for these patients, and recent advances in biologically based therapy. It provides a concise up-to-date reference for practitioners, students, and researchers.
Neurobiology of Exceptionality
Nurture or nature? Biology or environment? Why are some people intelligent, or personable, or creative and others obtuse, or shy, or unimaginative? Although each human being is a unique mixture of positive and negative traits and behaviors, the question remains: What is the neurobiological basis for each individual’s makeup? For example, why does one person suffer from a disorder (e.g., ADHD, autism, mental retardation) and another lives free of maladies?
Neuroanatomy for the Neuroscientist
Neurology, more than any other system of medicine, is rooted in the firm knowledge of basic science material (i.e., the anatomy, physiology, and pathology of the nervous system). This material enables students to readily arrive at diagnoses and to apply their knowledge at solving problems in clinical situations. Neuroanatomy for the Neuroscientist gives neuroscientists the tools to teach this material at levels appropriate for students at several levels of study, including undergraduate, graduate, dental, and medical school. The text also provides an updated approach to lesion localization in neurology, utilizing the techniques of computerized axial tomography (CT scanning), magnetic resonance imaging (MRI), and magnetic resonance angiography (MRA). Multiple illustrations demonstrating the value of these techniques in clinical neurology and neuroanatomical localization has been provided.
Neuroacanthocytosis Syndromes
Neuroacanthocytosis Syndromes is the first comprehensive review of a field that has not yet received the attention it deserves. Affecting the brain as well as the circulating red cells, these multi-system disorders in the past had often been mistaken for Huntington's disease. Recent breakthroughs have now identified the molecular basis of several of these. This volume grew out of the first international scientific meeting ever devoted to neuroacanthocytosis and provides in-depth information about the state of the art. Its thirty chapters were written by the leading authorities in the field to cover the clinical as well as the basic science perspective, including not only molecular genetics but also experimental pharmacology and cell membrane biology, among others. The book vehemently poses the question of how the membrane deformation of circulating red blood cells relates to degeneration of nerve cells in the brain, the basal ganglia, in particular. It provides a wealth of data that will help to solve an intriguing puzzle and ease the suffering of those affected by one of the neuroacanthocytosis syndromes.
Neural Networks in a Softcomputing Framework
This concise but comprehensive textbook provides a powerful and universal paradigm for information processing. Each chapter provides state-of-the-art descriptions of the important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms, are introduced. These are powerful tools for neural-network learning. Array signal processing problems are discussed in order to illustrate the applications of each neural-network model.
Neural Networks and Sea Time Series : Reconstruction and Extreme-Event Analysis
This book, a careful blend of theory and applications, is an excellent introduction to the use of ANN, which may encourage readers to try analogous approaches in other important application areas. Researchers, practitioners, and advanced graduate students in neural networks, hydraulic and marine engineering, prediction theory, and data analysis will benefit from the results and novel ideas presented in this useful resource.
Neural networks and deep learning
Covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems.
Neural Networks : Methodology and Applications
Neural networks represent a powerful data processing technique that has reached maturity and broad application. When clearly understood and appropriately used, they are a mandatory component in the toolbox of any engineer who wants make the best use of the available data, in order to build models, make predictions, mine data, recognize shapes or signals, etc. Ranging from theoretical foundations to real-life applications, this book is intended to provide engineers and researchers with clear methodologies for taking advantage of neural networks in industrial, financial or banking applications, many instances of which are presented in the book. For the benefit of readers wishing to gain deeper knowledge of the topics, the book features appendices that provide theoretical details for greater insight, and algorithmic details for efficient programming and implementation. The chapters have been written by experts ands seemlessly edited to present a coherent and comprehensive, yet not redundant, practically-oriented introduction.
Neural Networks : Computational Models and Applications
Neural Networks: Computational Models and Applications covers a wealth of important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. By presenting various computational models, this book is developed to provide readers with a quick but insightful understanding of the broad and rapidly growing areas in the neural networks domain. Besides laying down fundamentals on artificial neural networks, this book also studies biologically inspired neural networks. Some typical computational models are discussed, and subsequently applied to objection recognition, scene analysis and associative memory. The studies of bio-inspired models have important implications in computer vision and robotic navigation, as well as new efficient algorithms for image analysis.
Neural Network Theory
Neural Networks Theory is a major contribution to the neural networks literature. It is a treasure trove that should be mined by the thousands of researchers and practitioners worldwide who have not previously had access to the fruits of Soviet and Russian neural network research. Dr. Galushkin is to be congratulated and thanked for his completion of this monumental work; a book that only he could write. It is a major gift to the world.
Neural Network Driven Artificial Intelligence : Decision Making Based On Fuzzy Logic
Artificial Intelligence, Computer Science and Internet, Computer Science, Technology and Applications, Mathematics Research Developments
Neural Nets ; 16th Italian Workshop on Neural Nets, WIRN 2005, International workshop on natural and artificial immune systems, NAIS 2005, Vietri sul Mare, Italy, June 8-11, 2005, Revised Selected Papers
This book constitutes the thoroughly refereed postproceedings of the 16th Italian Workshop on Neural Nets, WIRN 2005, as well as the satellite International Workshop on Natural and Artificial Immune Systems, NAIS 2005, held in Vietri sul Mare, Italy in June 2005. The 41 revised papers presented together with a lecture by the winner of the Premio Caianiello award were carefully reviewed and improved during two rounds of selection and refereeing.
Neural Information Processing ; Vol. 4234 ; 13th International Conference, ICONIP 2006, Hong Kong, China, October 3-6, 2006, Proceedings, Part III
This book and its companion volumes constitute the Proceedings of the 13th - ternationalConferenceonNeuralInformationProcessing(ICONIP2006)heldin Hong Kong during October 3–6,2006. ICONIP is the annual ?agship conference oftheAsiaPaci?cNeuralNetworkAssembly(APNNA)withthepasteventsheld in Seoul (1994), Beijing (1995), Hong Kong (1996), Dunedin (1997), Kitakyushu (1998), Perth(1999), Taejon(2000), Shanghai(2001), Singapore(2002), Istanbul (2003), Calcutta(2004), andTaipei(2005). Overtheyears, ICONIPhasmatured into a well-established series of international conference on neural information processing and related ?elds in the Asia and Paci?cregions. Following the tra- tion, ICONIP 2006 provided an academic forum for the participants to diss- inate their new research ?ndings and discuss emerging areas of research.
Neural Information Processing ; Vol. 4232 ; 13th International Conference, ICONIP 2006, Hong Kong, China, October 3-6, 2006, Proceedings, Part I
This book and its companion volumes constitute the Proceedings of the 13th - ternationalConferenceonNeuralInformationProcessing(ICONIP2006)heldin Hong Kong during October 3–6,2006. ICONIP is the annual ?agship conference oftheAsiaPaci?cNeuralNetworkAssembly(APNNA)withthepasteventsheld in Seoul (1994), Beijing (1995), Hong Kong (1996), Dunedin (1997), Kitakyushu (1998), Perth(1999), Taejon(2000), Shanghai(2001), Singapore(2002), Istanbul (2003), Calcutta(2004), andTaipei(2005). Overtheyears, ICONIPhasmatured into a well-established series of international conference on neural information processing and related ?elds in the Asia and Paci?cregions. Following the tra- tion, ICONIP 2006 provided an academic forum for the participants to diss- inate their new research ?ndings and discuss emerging areas of research.
Neural Information Processing ; 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II
The 228 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. The 116 papers of the first volume are organized in topical sections on computational neuroscience, learning and memory, neural network models ,supervised /unsupervised/reinforcement learning, statistical learning algorithms, optimization algorithms, novel algorithms, as well as motor control and vision. The second volume contains 112 contributions related to statistical and pattern recognition algorithms, neuromorphic hardware and implementations, robotics, data mining and knowledge discovery, real world applications, cognitive and hybrid intelligent systems, bioinformatics, neuroinformatics, brain-conputer interfaces, and novel approaches.
Neural Information Processing ; 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I
The 228 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. The 116 papers of the first volume are organized in topical sections on computational neuroscience, learning and memory, neural network models, supervised/unsupervised/reinforcement learning, statistical learning algorithms, optimization algorithms, novel algorithms, as well as motor control and vision. The second volume contains 112 contributions related to statistical and pattern recognition algorithms, neuromorphic hardware and implementations, robotics, data mining and knowledge discovery, real world applications, cognitive and hybrid intelligent systems, bioinformatics, neuroinformatics, brain-conputer interfaces, and novel approaches.
Neural Engineering
Neural Engineering, Bioelectric Engineering Volume 2, contains reviews and discussions of contemporary and relevant topics by leading investigators in the field.
