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EBookClubs

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Book Introduction to Theoretical Neurobiology  Volume 2  Nonlinear and Stochastic Theories

Download or read book Introduction to Theoretical Neurobiology Volume 2 Nonlinear and Stochastic Theories written by Henry C. Tuckwell and published by Cambridge University Press. This book was released on 1988-04-29 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second part of this two-volume set contains advanced aspects of the quantitative theory of the dynamics of neurons. It begins with an introduction to the effects of reversal potentials on response to synaptic input. It then develops the theory of action potential generation based on the seminal Hodgkin-Huxley equations and gives methods for their solution in the space-clamped and nonspaceclamped cases. The remainder of the book discusses stochastic models of neural activity and ends with a statistical analysis of neuronal data with emphasis on spike trains. The mathematics is more complex in this volume than in the first volume and involves numerical methods of solution of partial differential equations and the statistical analysis of point processes.

Book Introduction to Theoretical Neurobiology  Linear cable theory and dendritic structure

Download or read book Introduction to Theoretical Neurobiology Linear cable theory and dendritic structure written by Henry Clavering Tuckwell and published by Cambridge University Press. This book was released on 1988 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explaining the basic properties of a neuron, this volume develops mathematical theories for the way neurons respond to the various stimuli they receive. It contains descriptions and analyses of the principal mathematical models, providing a brief review of the basic neuroanatomical and neurophysiological facts with the mathematical theories.

Book Stochastic Methods in Neuroscience

Download or read book Stochastic Methods in Neuroscience written by Carlo Laing and published by OUP Oxford. This book was released on 2009-09-24 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Great interest is now being shown in computational and mathematical neuroscience, fuelled in part by the rise in computing power, the ability to record large amounts of neurophysiological data, and advances in stochastic analysis. These techniques are leading to biophysically more realistic models. It has also become clear that both neuroscientists and mathematicians profit from collaborations in this exciting research area. Graduates and researchers in computational neuroscience and stochastic systems, and neuroscientists seeking to learn more about recent advances in the modelling and analysis of noisy neural systems, will benefit from this comprehensive overview. The series of self-contained chapters, each written by experts in their field, covers key topics such as: Markov chain models for ion channel release; stochastically forced single neurons and populations of neurons; statistical methods for parameter estimation; and the numerical approximation of these stochastic models. Each chapter gives an overview of a particular topic, including its history, important results in the area, and future challenges, and the text comes complete with a jargon-busting index of acronyms to allow readers to familiarize themselves with the language used.

Book Stochastic Processes in the Neurosciences

Download or read book Stochastic Processes in the Neurosciences written by Henry C. Tuckwell and published by SIAM. This book was released on 1989-01-01 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is centered on quantitative analysis of nerve-cell behavior. The work is foundational, with many higher order problems still remaining, especially in connection with neural networks. Thoroughly addressed topics include stochastic problems in neurobiology, and the treatment of the theory of related Markov processes.

Book Introduction to Theoretical Neurobiology  Volume 2  Nonlinear and Stochastic Theories

Download or read book Introduction to Theoretical Neurobiology Volume 2 Nonlinear and Stochastic Theories written by Henry C. Tuckwell and published by Cambridge University Press. This book was released on 1988-04-29 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second part of this two-volume set contains advanced aspects of the quantitative theory of the dynamics of neurons. It begins with an introduction to the effects of reversal potentials on response to synaptic input. It then develops the theory of action potential generation based on the seminal Hodgkin-Huxley equations and gives methods for their solution in the space-clamped and nonspaceclamped cases. The remainder of the book discusses stochastic models of neural activity and ends with a statistical analysis of neuronal data with emphasis on spike trains. The mathematics is more complex in this volume than in the first volume and involves numerical methods of solution of partial differential equations and the statistical analysis of point processes.

Book Stochastic Biomathematical Models

Download or read book Stochastic Biomathematical Models written by Mostafa Bachar and published by Springer. This book was released on 2012-10-19 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.

Book Handbook on Biological Networks

Download or read book Handbook on Biological Networks written by Stefano Boccaletti and published by World Scientific. This book was released on 2010 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networked systems are all around us. The accumulated evidence of systems as complex as a cell cannot be fully understood by studying only their isolated constituents, giving rise to a new area of interest in research OCo the study of complex networks . In a broad sense, biological networks have been one of the most studied networks, and the field has benefited from many important contributions. By understanding and modeling the structure of a biological network, a better perception of its dynamical and functional behavior is to be expected. This unique book compiles the most relevant results and novel insights provided by network theory in the biological sciences, ranging from the structure and dynamics of the brain to cellular and protein networks and to population-level biology. Sample Chapter(s). Chapter 1: Introduction (61 KB). Contents: Networks at the Cellular Level: The Structural Network Properties of Biological Systems (M Brilli & P Li); Dynamics of Multicellular Synthetic Gene Networks (E Ullner et al.); Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level (J Thakar & R Albert); Complexity of Boolean Dynamics in Simple Models of Signaling Networks and in Real Genetic Networks (A D az-Guilera & R ulvarez-Buylla); Geometry and Topology of Folding Landscapes (L Bongini & L Casetti); Elastic Network Models for Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses (T R Lezon et al.); Metabolic Networks (M C Palumbo et al.); Brain Networks: The Human Brain Network (O Sporns); Brain Network Analysis from High-Resolution EEG Signals (F De Vico Fallani & F Babiloni); An Optimization Approach to the Structure of the Neuronal layout of C elegans (A Arenas et al.); Cultured Neuronal Networks Express Complex Patterns of Activity and Morphological Memory (N Raichman et al.); Synchrony and Precise Timing in Complex Neural Networks (R-M Memmesheimer & M Timme); Networks at the Individual and Population Levels: Ideas for Moving Beyond Structure to Dynamics of Ecological Networks (D B Stouffer et al.); Evolutionary Models for Simple Biosystems (F Bagnoli); Evolution of Cooperation in Adaptive Social Networks (S Van Segbroeck et al.); From Animal Collectives and Complex Networks to Decentralized Motion Control Strategies (A Buscarino et al.); Interplay of Network State and Topology in Epidemic Dynamics (T Gross). Readership: Advanced undergraduates, graduate students and researchers interested in the study of complex networks in a wide range of biological processes and systems."

Book Cellular Biophysics and Modeling

Download or read book Cellular Biophysics and Modeling written by Greg Conradi Smith and published by Cambridge University Press. This book was released on 2019-03-14 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: What every neuroscientist should know about the mathematical modeling of excitable cells. Combining empirical physiology and nonlinear dynamics, this text provides an introduction to the simulation and modeling of dynamic phenomena in cell biology and neuroscience. It introduces mathematical modeling techniques alongside cellular electrophysiology. Topics include membrane transport and diffusion, the biophysics of excitable membranes, the gating of voltage and ligand-gated ion channels, intracellular calcium signalling, and electrical bursting in neurons and other excitable cell types. It introduces mathematical modeling techniques such as ordinary differential equations, phase plane, and bifurcation analysis of single-compartment neuron models. With analytical and computational problem sets, this book is suitable for life sciences majors, in biology to neuroscience, with one year of calculus, as well as graduate students looking for a primer on membrane excitability and calcium signalling.

Book Modern Techniques in Neuroscience Research

Download or read book Modern Techniques in Neuroscience Research written by Uwe Windhorst and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 1336 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of the techniques used in modern neuroscience research with the emphasis on showing how different techniques can optimally be combined in the study of problems that arise at some levels of nervous system organization. This is essentially a working tool for the scientist in the laboratory and clinic, providing detailed step-by-step protocols with tips and recommendations. Most chapters and protocols are organized such that they can be used independently, while cross-references between the chapters, a glossary, a list of suppliers and appendices provide further help.

Book Foundations of Cellular Neurophysiology

Download or read book Foundations of Cellular Neurophysiology written by Daniel Johnston and published by MIT Press. This book was released on 1994-11-02 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: with simulations and illustrations by Richard Gray Problem solving is an indispensable part of learning a quantitative science such as neurophysiology. This text for graduate and advanced undergraduate students in neuroscience, physiology, biophysics, and computational neuroscience provides comprehensive, mathematically sophisticated descriptions of modern principles of cellular neurophysiology. It is the only neurophysiology text that gives detailed derivations of equations, worked examples, and homework problem sets (with complete answers). Developed from notes for the course that the authors have taught since 1983, Foundations of Cellular Neurophysiology covers cellular neurophysiology (also some material at the molecular and systems levels) from its physical and mathematical foundations in a way that is far more rigorous than other commonly used texts in this area.

Book Elementary Applications of Probability Theory

Download or read book Elementary Applications of Probability Theory written by Henry C. Tuckwell and published by Routledge. This book was released on 2018-02-06 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a clear and straightforward introduction to applications of probability theory with examples given in the biological sciences and engineering. The first chapter contains a summary of basic probability theory. Chapters two to five deal with random variables and their applications. Topics covered include geometric probability, estimation of animal and plant populations, reliability theory and computer simulation. Chapter six contains a lucid account of the convergence of sequences of random variables, with emphasis on the central limit theorem and the weak law of numbers. The next four chapters introduce random processes, including random walks and Markov chains illustrated by examples in population genetics and population growth. This edition also includes two chapters which introduce, in a manifestly readable fashion, the topic of stochastic differential equations and their applications.

Book Proceedings of the First Brazilian Symposium on Mathematical and Computational Biology

Download or read book Proceedings of the First Brazilian Symposium on Mathematical and Computational Biology written by Rubem Mondaini and published by Editora E-papers. This book was released on 2001 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Analysis of Neural Data

Download or read book Analysis of Neural Data written by Robert E. Kass and published by Springer. This book was released on 2014-07-08 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

Book Probabilistic Spiking Neuronal Nets

Download or read book Probabilistic Spiking Neuronal Nets written by Antonio Galves and published by Springer Nature. This book was released on with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Single Neuron Computation

Download or read book Single Neuron Computation written by Thomas M. McKenna and published by Academic Press. This book was released on 2014-05-19 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the information processing performed by single neurons leads to an understanding of circuit- and systems-level activity. From the standpoint of artificial neural networks (ANNs), a single real neuron is as complex an operational unit as an entire ANN, and formalizing the complex computations performed by real neurons is essential to the design of enhanced processor elements for use in the next generation of ANNs.The book covers computation in dendrites and spines, computational aspects of ion channels, synapses, patterned discharge and multistate neurons, and stochastic models of neuron dynamics. It is the most up-to-date presentation of biophysical and computational methods.

Book Computational Neuroscience

Download or read book Computational Neuroscience written by Jianfeng Feng and published by CRC Press. This book was released on 2003-10-20 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: How does the brain work? After a century of research, we still lack a coherent view of how neurons process signals and control our activities. But as the field of computational neuroscience continues to evolve, we find that it provides a theoretical foundation and a set of technological approaches that can significantly enhance our understanding.