Principles Of Neural Science

Principles of Neural Science, 5e describes our current understanding of how the nerves, brain, and mind function. From molecules and cells to anatomic structures and systems to senses and cognitive functions, this comprehensive reference covers every aspect of neuroscience.

This text is an introduction to the brain, its structure, function, development, and control of behavior, with expanded treatment of channel mechanisms, development of the nervous system, and the genetic basis of neurological and psychiatric disease. (Midwest).

Two distinguished neuroscientists distil general principles from more than a century of scientific study, "reverse engineering" the brain to understand its design. Neuroscience research has exploded, with more than fifty thousand neuroscientists applying increasingly advanced methods. A mountain of new facts and mechanisms has emerged. And yet a principled framework to organize this knowledge has been missing. In this book, Peter Sterling and Simon Laughlin, two leading neuroscientists, strive to fill this gap, outlining a set of organizing principles to explain the whys of neural design that allow the brain to compute so efficiently. Setting out to "reverse engineer" the brain--disassembling it to understand it--Sterling and Laughlin first consider why an animal should need a brain, tracing computational abilities from bacterium to protozoan to worm. They examine bigger brains and the advantages of "anticipatory regulation"; identify constraints on neural design and the need to "nanofy"; and demonstrate the routes to efficiency in an integrated molecular system, phototransduction. They show that the principles of neural design at finer scales and lower levels apply at larger scales and higher levels; describe neural wiring efficiency; and discuss learning as a principle of biological design that includes "save only what is needed." Sterling and Laughlin avoid speculation about how the brain might work and endeavor to make sense of what is already known. Their distinctive contribution is to gather a coherent set of basic rules and exemplify them across spatial and functional scales.

The gold standard of neuroscience texts—updated with hundreds of brand-new images and fully revised content in every chapter With 300 new illustrations, diagrams, and radiology studies including PET scans, Principles of Neural Science, 6th Edition is the definitive guide for neuroscientists, neurologists, psychiatrists, students, and residents. Highly detailed chapters on stroke, Parkinson’s, and MS build your expertise on these critical topics. Radiological studies the authors have chosen explain what’s most important to know and understand for each type of stroke, progressive MS, or non-progressive MS. Features 2,200 images, including 300 new color illustrations, diagrams, and radiology studies (including PET scans) NEW: This edition now features only two contributors per chapter and are mostly U.S.-based NEW: Number of chapters streamlined down from 67 to 60 NEW: Chapter on Navigation and Spatial Memory NEW: New images in every chapter!

Principles of Neurobiology, Second Edition presents the major concepts of neuroscience with an emphasis on how we know what we know. The text is organized around a series of key experiments to illustrate how scientific progress is made and helps upper-level undergraduate and graduate students discover the relevant primary literature. Written by a single author in a clear and consistent writing style, each topic builds in complexity from electrophysiology to molecular genetics to systems level in a highly integrative approach. Students can fully engage with the content via thematically linked chapters and will be able to read the book in its entirety in a semester-long course. Principles of Neurobiology is accompanied by a rich package of online student and instructor resources including animations, figures in PowerPoint, and a Question Bank for adopting instructors.

This textbook presents the fundamental principles of neuroscience and its effect on behavior. Neuroscience is the scientific study of the nervous system. Topics will include: principles of brain organization; structure and ultrastructure of neurons; neurophysiology and biophysics of excitable cells; synaptic transmission; neurotransmitter systems and neurochemistry; molecular biology of neurons; development and plasticity of the brain; aging and diseases of the nervous system; organization of sensory and motor systems; structure and function of cerebral cortex; modeling of neural systems. It also examines such topics as mammalian sensory, motor, regulatory, and motivational mechanisms involved in the control of behavior, and higher mental processes such as those involved in language and memory.

A Nobel Prize–winning neuroscientist’s probing investigation of what brain disorders can tell us about human nature Eric R. Kandel, the winner of the Nobel Prize in Physiology or Medicine for his foundational research into memory storage in the brain, is one of the pioneers of modern brain science. His work continues to shape our understanding of how learning and memory work and to break down age-old barriers between the sciences and the arts. In his seminal new book, The Disordered Mind, Kandel draws on a lifetime of pathbreaking research and the work of many other leading neuroscientists to take us on an unusual tour of the brain. He confronts one of the most difficult questions we face: How does our mind, our individual sense of self, emerge from the physical matter of the brain? The brain’s 86 billion neurons communicate with one another through very precise connections. But sometimes those connections are disrupted. The brain processes that give rise to our mind can become disordered, resulting in diseases such as autism, depression, schizophrenia, Parkinson’s, addiction, and post-traumatic stress disorder. While these disruptions bring great suffering, they can also reveal the mysteries of how the brain produces our most fundamental experiences and capabilities—the very nature of what it means to be human. Studies of autism illuminate the neurological foundations of our social instincts; research into depression offers important insights on emotions and the integrity of the self; and paradigm-shifting work on addiction has led to a new understanding of the relationship between pleasure and willpower. By studying disruptions to typical brain functioning and exploring their potential treatments, we will deepen our understanding of thought, feeling, behavior, memory, and creativity. Only then can we grapple with the big question of how billions of neurons generate consciousness itself.

In this richly illustrated book, it is shown how Shannon's mathematical theory of information defines absolute limits on neural efficiency; limits which ultimately determine the neuroanatomical microstructure of the eye and brain. Written in an informal style this is an ideal introduction to cutting-edge research in neural information theory.

Understanding how populations of neurons encode information is the challenge faced by researchers in the field of neural coding. Focusing on the many mysteries and marvels of the mind has prompted a prominent team of experts in the field to put their heads together and fire up a book on the subject. Simply titled Principles of Neural Coding, this book covers the complexities of this discipline. It centers on some of the major developments in this area and presents a complete assessment of how neurons in the brain encode information. The book collaborators contribute various chapters that describe results in different systems (visual, auditory, somatosensory perception, etc.) and different species (monkeys, rats, humans, etc). Concentrating on the recording and analysis of the firing of single and multiple neurons, and the analysis and recording of other integrative measures of network activity and network states—such as local field potentials or current source densities—is the basis of the introductory chapters. Provides a comprehensive and interdisciplinary approach Describes topics of interest to a wide range of researchers The book then moves forward with the description of the principles of neural coding for different functions and in different species and concludes with theoretical and modeling works describing how information processing functions are implemented. The text not only contains the most important experimental findings, but gives an overview of the main methodological aspects for studying neural coding. In addition, the book describes alternative approaches based on simulations with neural networks and in silico modeling in this highly interdisciplinary topic. It can serve as an important reference to students and professionals.

Development of the Nervous System, Second Edition has been thoroughly revised and updated since the publication of the First Edition. It presents a broad outline of neural development principles as exemplified by key experiments and observations from past and recent times. The text is organized along a development pathway from the induction of the neural primordium to the emergence of behavior. It covers all the major topics including the patterning and growth of the nervous system, neuronal determination, axonal navigation and targeting, synapse formation and plasticity, and neuronal survival and death. This new text reflects the complete modernization of the field achieved through the use of model organisms and the intensive application of molecular and genetic approaches. The original, artist-rendered drawings from the First Edition have all been redone and colorized to so that the entire text is in full color. This new edition is an excellent textbook for undergraduate and graduate level students in courses such as Neuroscience, Medicine, Psychology, Biochemistry, Pharmacology, and Developmental Biology. Updates information including all the new developments made in the field since the first edition Now in full color throughout, with the original, artist-rendered drawings from the first edition completely redone, revised, colorized, and updated

"The companion volume to the new, fourth edition of Kandel, Schwartz, and Jessell's Principles of Neural Science, this engaging book bridges the gap between basic science and clinical medicine, emphasizing the real-world relevance of neurobiology to clinical decision-making.".

Cognitive Neuroscience and Psychotherapy provides a bionetwork theory unifying empirical evidence in cognitive neuroscience and psychopathology to explain how emotion, learning, and reinforcement affect personality and its extremes. The book uses the theory to explain research results in both disciplines and to predict future findings, as well as to suggest what the theory and evidence say about how we should be treating disorders for maximum effectiveness. While theoretical in nature, the book has practical applications, and takes a mathematical approach to proving its own theorems. The book is unapologetically physical in nature, describing everything we think and feel by way of physical mechanisms and reactions in the brain. This unique marrying of cognitive neuroscience and clinical psychology provides an opportunity to better understand both. Unifying theory for cognitive neuroscience and clinical psychology Describes the brain in physical terms via mechanistic processes Systematically uses the theory to explain empirical evidence in both disciplines Theory has practical applications for psychotherapy Ancillary material may be found at: http://booksite.elsevier.com/9780124200715 including an additional chapter and supplements

Neuroscience is, by definition, a multidisciplinary field: some scientists study genes and proteins at the molecular level while others study neural circuitry using electrophysiology and high-resolution optics. A single topic can be studied using techniques from genetics, imaging, biochemistry, or electrophysiology. Therefore, it can be daunting for young scientists or anyone new to neuroscience to learn how to read the primary literature and develop their own experiments. This volume addresses that gap, gathering multidisciplinary knowledge and providing tools for understanding the neuroscience techniques that are essential to the field, and allowing the reader to design experiments in a variety of neuroscience disciplines. Written to provide a "hands-on" approach for graduate students, postdocs, or anyone new to the neurosciences Techniques within one field are compared, allowing readers to select the best techniques for their own work Includes key articles, books, and protocols for additional detailed study Data analysis boxes in each chapter help with data interpretation and offer guidelines on how best to represent results Walk-through boxes guide readers step-by-step through experiments

A Primer with MATLAB® and PythonTM present important information on the emergence of the use of Python, a more general purpose option to MATLAB, the preferred computation language for scientific computing and analysis in neuroscience. This book addresses the snake in the room by providing a beginner’s introduction to the principles of computation and data analysis in neuroscience, using both Python and MATLAB, giving readers the ability to transcend platform tribalism and enable coding versatility. Includes discussions of both MATLAB and Python in parallel Introduces the canonical data analysis cascade, standardizing the data analysis flow Presents tactics that strategically, tactically, and algorithmically help improve the organization of code

Turn to Fundamental Neuroscience for a thorough, clinically relevant understanding of this complicated subject! Integrated coverage of neuroanatomy, physiology, and pharmacology, with a particular emphasis on systems neurobiology, effectively prepares you for your courses, exams, and beyond. Easily comprehend and retain complex material thanks to the expert instruction of Professor Duane Haines, recipient of the Henry Gray/Elsevier Distinguished Teacher Award from the American Association of Anatomists and the Distinguished Teacher Award from the Association of American Colleges. Access the complete contents online at www.studentconsult.com, plus 150 USMLE-style review questions, sectional images correlated with the anatomical diagrams within the text, and more. Grasp important anatomical concepts and their clinical applications thanks to correlated state-of-the-art imaging examples, anatomical diagrams, and histology photos. Retain key information and efficiently study for your exams with clinical highlights integrated and emphasized within the text.

Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition — all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained. The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining. Contents:Introduction and Role of Artificial Neural NetworksFundamentals of Biological Neural NetworksBasic Principles of ANNs and Their Early StructuresThe PerceptronThe MadalineBack PropagationHopfield NetworksCounter PropagationLarge Scale Memory Storage and Retrieval (LAMSTAR) NetworkAdaptive Resonance TheoryThe Cognitron and the NeocognitronStatistical TrainingRecurrent (Time Cycling) Back Propagation Networks Readership: Graduate and advanced senior students in artificial intelligence, pattern recognition & image analysis, neural networks, computational economics and finance, and biomedical engineering. Keywords:Neural Networks;Mathematical Derivations;Source Codes;Medical Applications;Data Mining;Cell-Shape Recognition;Micro-Trading

Includes bibliographical references and index.