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The classical Melnikov method provides information on the behavior of deterministic planar systems that may exhibit transitions, i.e. escapes from and captures into preferred regions of phase space. This book develops a unified treatment of deterministic and stochastic systems that extends the applicability of the Melnikov method to physically realizable stochastic planar systems with additive, state-dependent, white, colored, or dichotomous noise. The extended Melnikov method yields the novel result that motions with transitions are chaotic regardless of whether the excitation is deterministic or stochastic. It explains the role in the occurrence of transitions of the characteristics of the system and its deterministic or stochastic excitation, and is a powerful modeling and identification tool. The book is designed primarily for readers interested in applications. The level of preparation required corresponds to the equivalent of a first-year graduate course in applied mathematics. No previous exposure to dynamical systems theory or the theory of stochastic processes is required. The theoretical prerequisites and developments are presented in the first part of the book. The second part of the book is devoted to applications, ranging from physics to mechanical engineering, naval architecture, oceanography, nonlinear control, stochastic resonance, and neurophysiology.

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The brain is the most complex computational machine known to science, even though its components (neurons) are slow and unreliable compared to a laptop computer. In this richly illustrated book, Shannon's mathematical theory of information is used to explore the metabolic efficiency of neurons, with special reference to visual perception. Evidence from a diverse range of research papers is used to show how information theory defines absolute limits on neural efficiency; limits which ultimately determine the neuroanatomical microstructure of the eye and brain. Written in an informal style, with a comprehensive glossary, tutorial appendices, explainer boxes, and a list of annotated Further Readings, this book is an ideal introduction to cutting-edge research in neural information theory.

The brain is the most complex computational machine known to science, even though its components (neurons) are slow and unreliable compared to a laptop computer. In this richly illustrated book, Shannon's mathematical theory of information is used to explore the computational efficiency of neurons, with special reference to visual perception and the efficient coding hypothesis. Evidence from a diverse range of research papers is used to show how information theory defines absolute limits on neural processing; limits which ultimately determine the neuroanatomical microstructure of the eye and brain. Written in an informal style, with a comprehensive glossary, tutorial appendices, and a list of annotated Further Readings, this book is an ideal introduction to the principles of neural information theory.

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The brain is the most complex computational machine known to science, even though its components (neurons) are slow and unreliable compared to a laptop computer. In this richly illustrated book, Shannon's mathematical theory of information is used to explore the metabolic efficiency of neurons, with special reference to visual perception. Evidence from a diverse range of research papers is used to show how information theory defines absolute limits on neural efficiency; limits which ultimately determine the neuroanatomical microstructure of the eye and brain. Written in an informal style, with a comprehensive glossary, tutorial appendices, explainer boxes, and a list of annotated Further Readings, this book is an ideal introduction to cutting-edge research in neural information theory.

Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes.Key topics covered include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; chemical and electrical synapses and how to treat them from a computational point of view; nonlinear interactions of synaptic input in passive and active dendritic trees; the Hodgkin-Huxley model of action potential generation and propagation; phase space analysis; linking stochastic ionic channels to membrane-dependent currents; calcium and potassium currents and their role in information processing; the role of diffusion, buffering and binding of calcium, and other messenger systems in information processing and storage; short- and long-term models of synaptic plasticity; simplified models of single cells; stochastic aspects of neuronal firing; the nature of the neuronal code; and unconventional models of sub-cellular computation.Biophysics of Computation: Information Processing in Single Neurons serves as an ideal text for advanced undergraduate and graduate courses in cellular biophysics, computational neuroscience, and neural networks, and will appeal to students and professionals in neuroscience, electrical and computer engineering, and physics.

Fully updated and revised according to student feedback, the sixth edition of Mayo Clinic Medical Neurosciences: Organized by Neurologic System and Level provides a systematic approach to anatomy, physiology, and pathology of the nervous system inspired by the neurologist's approach to solving clinical problems. This volume has 4 sections: 1) an overview of the neurosciences necessary for understanding anatomical localization and pathophysiologic characterization of neurologic disorders; 2) an approach to localizing lesions in the 7 longitudinal systems of the nervous system; 3) an approach to localizing lesions in the 4 horizontal levels of the nervous system; and 4) a collection of clinical problems. This book provides the neuroscience framework to support the neurologist in a clinical setting and is also a great resource for neurology and psychiatry board certifications. This is the perfect guide for all medical students and neurology, psychiatry, and physical medicine residents at early stages of training. New to This Edition - A chapter devoted to multiple-choice questions for self-assessment- Discussion of emerging concepts in molecular, cellular, and system neurosciences- New chapters on emotion and consciousness systems- Incorporation of new discoveries in neuroimaging and an appendix for tables of medications commonly used to treat neurologic disorders

The aim of this book is to bring together social scientists, cognitive scientists, psychologists, neuroscientists, neuropsychologists and others to promote a dialogue about the variety of processes involved in social cognition, as well as the relevance of mirroring neural systems to those processes. Social cognition is a broad discipline that encompasses many issues not yet adequately addressed by neurobiologists. Yet, it is a strong belief that framing these issues in terms of the neural basis of social cognition, especially within an evolutionary perspective, can be a very fruitful strategy. This book includes some of the leading thinkers in the nascent field of mirroring processes and reflects the authors’ attempts to till common ground from a variety of perspectives. The book raises contrary views and addresses some of the most vexing yet core questions in the field – providing the basis for extended discussion among interested readers and laying down guidelines for future research. It has been argued that interaction with members of one’s own social group enhances cognitive development in primates and especially humans (Barrett & Henzi, 2005). Byrne and Whiten (1988), Donald (1991), and others have speculated that abilities such as cooperation, deception, and imitation led to increasingly complex social interactions among primates resulting in a tremendous expansion of the cerebral cortex. The evolutionary significance of an imitation capability in primates is matched by its ontological consequences.

Fully updated and revised according to student feedback, the sixth edition of Mayo Clinic Medical Neurosciences: Organized by Neurologic System and Level provides a systematic approach to anatomy, physiology, and pathology of the nervous system inspired by the neurologist's approach to solving clinical problems. This volume has 4 sections: 1) an overview of the neurosciences necessary for understanding anatomical localization and pathophysiologic characterization of neurologic disorders; 2) an approach to localizing lesions in the 7 longitudinal systems of the nervous system; 3) an approach to localizing lesions in the 4 horizontal levels of the nervous system; and 4) a collection of clinical problems. This book provides the neuroscience framework to support the neurologist in a clinical setting and is also a great resource for neurology and psychiatry board certifications. This is the perfect guide for all medical students and neurology, psychiatry, and physical medicine residents at early stages of training. New to This Edition - A chapter devoted to multiple-choice questions for self-assessment- Discussion of emerging concepts in molecular, cellular, and system neurosciences- New chapters on emotion and consciousness systems- Incorporation of new discoveries in neuroimaging and an appendix for tables of medications commonly used to treat neurologic disorders

The aim of this book is to bring together social scientists, cognitive scientists, psychologists, neuroscientists, neuropsychologists and others to promote a dialogue about the variety of processes involved in social cognition, as well as the relevance of mirroring neural systems to those processes. Social cognition is a broad discipline that encompasses many issues not yet adequately addressed by neurobiologists. Yet, it is a strong belief that framing these issues in terms of the neural basis of social cognition, especially within an evolutionary perspective, can be a very fruitful strategy. This book includes some of the leading thinkers in the nascent field of mirroring processes and reflects the authors’ attempts to till common ground from a variety of perspectives. The book raises contrary views and addresses some of the most vexing yet core questions in the field – providing the basis for extended discussion among interested readers and laying down guidelines for future research. It has been argued that interaction with members of one’s own social group enhances cognitive development in primates and especially humans (Barrett & Henzi, 2005). Byrne and Whiten (1988), Donald (1991), and others have speculated that abilities such as cooperation, deception, and imitation led to increasingly complex social interactions among primates resulting in a tremendous expansion of the cerebral cortex. The evolutionary significance of an imitation capability in primates is matched by its ontological consequences.

Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory. The book is divided into three parts. Part I discusses the relationship between sensory stimuli and neural responses, focusing on the representation of information by the spiking activity of neurons. Part II discusses the modeling of neurons and neural circuits on the basis of cellular and synaptic biophysics. Part III analyzes the role of plasticity in development and learning. An appendix covers the mathematical methods used, and exercises are available on the book's Web site.

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Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting ...

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The classical Melnikov method provides information on the behavior of deterministic planar systems that may exhibit transitions, i.e. escapes from and captures into preferred regions of phase space. This book develops a unified treatment of deterministic and stochastic systems that extends the applicability of the Melnikov method to physically realizable stochastic planar systems with additive, state-dependent, white, colored, or dichotomous noise. The extended Melnikov method yields the novel result that motions with transitions are chaotic regardless of whether the excitation is deterministic or stochastic. It explains the role in the occurrence of transitions of the characteristics of the system and its deterministic or stochastic excitation, and is a powerful modeling and identification tool. The book is designed primarily for readers interested in applications. The level of preparation required corresponds to the equivalent of a first-year graduate course in applied mathematics. No previous exposure to dynamical systems theory or the theory of stochastic processes is required. The theoretical prerequisites and developments are presented in the first part of the book. The second part of the book is devoted to applications, ranging from physics to mechanical engineering, naval architecture, oceanography, nonlinear control, stochastic resonance, and neurophysiology.

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With the research summarized in this monumental two volume treatise, Santiago Ramon y Cajal founded modern neuroscience and thus joined Darwin and Pasteur as the leading biologists of the 19th century. Starting around 1887, Cajal refined a neurological staining method developed almost 15 years earlier by the Italian histologist Camillo Golgi, and applied it first to relatively orderly parts of the nervous systems like the cerebellum, spinal cord, and retina. The conclusions he drew about the organization of neural circuits were, however, diametrically opposed to those advocated by Golgi, spurring an acrimonious debate that lasted well after the two shared the Nobel Prize in 1906. Early on, Cajal concluded that neural circuits are made up of individual units or nerve cells and interact by way of contact, whereas Golgi believed that such circuits are formed by a reticulum or net of contiguous nerve cells. Cajal was the first to see how neurons interact in the brain, laying the foundation for what came to be known as the neuron doctrine. His second great contribution was the ability to predict the direction of information flow in neural circuits based strictly on morphological criteria: dendrites and soma form the input side of a neuron while the axon forms its output side. This became known as the functional polarity hypothesis.Using these two foundation stones, Cajal went on to analyze systematically all parts of the mammalian nervous system, along with selected parts in all classes of vertebrates. A synthesis of that work, this volume, which is accompanied by over 1,000 original illustrations, is based almost entirely on personal observation and offers a wealth of factual, historical, and theoretical information.

Mindleap: A Fresh View of Education Empowered by Neuroscience and Systems Thinking 0.55

Physical therapist Adriaan Louw's Why You Hurt: Pain Neuroscience Education System is an interactive tool that will help you engage in meaningful discussions with your patients. The system refines complex neuroscience into easily internalized metaphors, examples and images to efficiently teach your patients what pain really is and how it works.Features:* Over a dozen versatile education sessions cover a wide variety of patients. 120+ illustrated education cards are intuitively separated into common chronic pain topics.* Teaching cues guide each session. Beginners can deliver the cues directly; after practice, cues function as guidelines.* Homework promotes deep learning and empowers patients with an active role. Includes 50 reproducible homework cards; photocopy the cards or download electronic versions*.* Pain questionnaire cards supplement education sessions or homework. 12 questions help unveil how patients conceptualize pain.* Teaching index ensures accurate selection of session topic. It details each section's message and offers a list of associated clinical issues.* Instructions and background of pain neuroscience education. Here's the how and why of PNE, including the impressive research behind it.Adriaan Louw's Why You Hurt system is much more than pain flashcards. This integrated system, based on best evidence research, gives you the knowledge and tools to treat chronic pain patients right out of the box.System includes 120+ full-color, two-sided education cards with teaching cues and scientific support, 50 reproducible and downloadable homework cards, 12 pain questionnaire cards, detailed instructions, discussion of PNE and a teaching index. Cards measure 8.5 inches x 6.5 inches.*This is the printed version only. A digital version is available exclusively through OPTP.