Mathematical Foundations of Neuroscience

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  • Author : G. Bard Ermentrout
  • Publisher : Springer Science & Business Media
  • Pages : 422 pages
  • ISBN : 0387877088
  • Rating : /5 from reviews
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Download or Read online Mathematical Foundations of Neuroscience full in PDF, ePub and kindle. this book written by G. Bard Ermentrout and published by Springer Science & Business Media which was released on 01 July 2010 with total page 422 pages. We cannot guarantee that Mathematical Foundations of Neuroscience book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. This book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical approaches to understand patterns of neuronal activity seen in experiments and models of neuronal behavior. The intended audience is researchers interested in applying mathematics to important problems in neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The authors take a very broad approach and use many different methods to solve and understand complex models of neurons and circuits. They explain and combine numerical, analytical, dynamical systems and perturbation methods to produce a modern approach to the types of model equations that arise in neuroscience. There are extensive chapters on the role of noise, multiple time scales and spatial interactions in generating complex activity patterns found in experiments. The early chapters require little more than basic calculus and some elementary differential equations and can form the core of a computational neuroscience course. Later chapters can be used as a basis for a graduate class and as a source for current research in mathematical neuroscience. The book contains a large number of illustrations, chapter summaries and hundreds of exercises which are motivated by issues that arise in biology, and involve both computation and analysis. Bard Ermentrout is Professor of Computational Biology and Professor of Mathematics at the University of Pittsburgh. David Terman is Professor of Mathematics at the Ohio State University.

Mathematical Foundations of Neuroscience

Mathematical Foundations of Neuroscience
  • Author : G. Bard Ermentrout,David H. Terman
  • Publisher : Springer Science & Business Media
  • Release : 01 July 2010
GET THIS BOOK Mathematical Foundations of Neuroscience

This book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical approaches to understand patterns of neuronal activity seen in experiments and models of neuronal behavior. The intended audience is researchers interested in applying mathematics to important problems in neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The authors take a very broad approach and use many different methods to solve

Mathematical Neuroscience

Mathematical Neuroscience
  • Author : Stanislaw Brzychczy,Roman R. Poznanski
  • Publisher : Academic Press
  • Release : 16 August 2013
GET THIS BOOK Mathematical Neuroscience

Mathematical Neuroscience is a book for mathematical biologists seeking to discover the complexities of brain dynamics in an integrative way. It is the first research monograph devoted exclusively to the theory and methods of nonlinear analysis of infinite systems based on functional analysis techniques arising in modern mathematics. Neural models that describe the spatio-temporal evolution of coarse-grained variables—such as synaptic or firing rate activity in populations of neurons —and often take the form of integro-differential equations would not normally

Tutorials in Mathematical Biosciences I

Tutorials in Mathematical Biosciences I
  • Author : Alla Borisyuk,G. Bard Ermentrout,Avner Friedman,David H. Terman
  • Publisher : Springer Science & Business Media
  • Release : 18 February 2005
GET THIS BOOK Tutorials in Mathematical Biosciences I

This volume introduces some basic theories on computational neuroscience. Chapter 1 is a brief introduction to neurons, tailored to the subsequent chapters. Chapter 2 is a self-contained introduction to dynamical systems and bifurcation theory, oriented towards neuronal dynamics. The theory is illustrated with a model of Parkinson's disease. Chapter 3 reviews the theory of coupled neural oscillators observed throughout the nervous systems at all levels; it describes how oscillations arise, what pattern they take, and how they depend on excitory or inhibitory synaptic

Mathematics for Neuroscientists

Mathematics for Neuroscientists
  • Author : Fabrizio Gabbiani,Steven James Cox
  • Publisher : Academic Press
  • Release : 21 March 2017
GET THIS BOOK Mathematics for Neuroscientists

Mathematics for Neuroscientists, Second Edition, presents a comprehensive introduction to mathematical and computational methods used in neuroscience to describe and model neural components of the brain from ion channels to single neurons, neural networks and their relation to behavior. The book contains more than 200 figures generated using Matlab code available to the student and scholar. Mathematical concepts are introduced hand in hand with neuroscience, emphasizing the connection between experimental results and theory. Fully revised material and corrected text Additional chapters

Mathematical and Theoretical Neuroscience

Mathematical and Theoretical Neuroscience
  • Author : Giovanni Naldi,Thierry Nieus
  • Publisher : Springer
  • Release : 20 March 2018
GET THIS BOOK Mathematical and Theoretical Neuroscience

This volume gathers contributions from theoretical, experimental and computational researchers who are working on various topics in theoretical/computational/mathematical neuroscience. The focus is on mathematical modeling, analytical and numerical topics, and statistical analysis in neuroscience with applications. The following subjects are considered: mathematical modelling in Neuroscience, analytical and numerical topics; statistical analysis in Neuroscience; Neural Networks; Theoretical Neuroscience. The book is addressed to researchers involved in mathematical models applied to neuroscience.

Advances in Cognitive Neurodynamics III

Advances in Cognitive Neurodynamics  III
  • Author : Yoko Yamaguchi
  • Publisher : Springer Science & Business Media
  • Release : 08 April 2013
GET THIS BOOK Advances in Cognitive Neurodynamics III

Within our knowledge, the series of the International Conference on Cognitive Neurodynamics (ICCN) is the only conference series dedicating to cognitive neurodynamis. This volume is the proceedings of the 3rd International Conference on Cognitive Neurodynamics held in 2011, which reviews the progress in this field since the 1st ICCN - 2007. The topics include: Neural coding and realistic neural network dynamics, Neural population dynamics, Firing Oscillations and Patterns in Neuronal Networks, Brain imaging, EEG, MEG, Sensory and Motor Dynamics, Global cognitive function,

Mathematics for Neuroscientists

Mathematics for Neuroscientists
  • Author : Fabrizio Gabbiani,Steven James Cox
  • Publisher : Academic Press
  • Release : 16 September 2010
GET THIS BOOK Mathematics for Neuroscientists

Virtually all scientific problems in neuroscience require mathematical analysis, and all neuroscientists are increasingly required to have a significant understanding of mathematical methods. There is currently no comprehensive, integrated introductory book on the use of mathematics in neuroscience; existing books either concentrate solely on theoretical modeling or discuss mathematical concepts for the treatment of very specific problems. This book fills this need by systematically introducing mathematical and computational tools in precisely the contexts that first established their importance for neuroscience.

An Introduction to Mathematical Modeling in Physiology Cell Biology and Immunology

An Introduction to Mathematical Modeling in Physiology  Cell Biology  and Immunology
  • Author : James Sneyd,American Mathematical Society
  • Publisher : American Mathematical Soc.
  • Release : 21 January 2022
GET THIS BOOK An Introduction to Mathematical Modeling in Physiology Cell Biology and Immunology

In many respects, biology is the new frontier for applied mathematicians. This book demonstrates the important role mathematics plays in the study of some biological problems. It introduces mathematicians to the biological sciences and provides enough mathematics for bioscientists to appreciate the utility of the modelling approach. The book presents a number of diverse topics, such as neurophysiology, cell biology, immunology, and human genetics. It examines how research is done,what mathematics is used, what the outstanding questions are, and

Math Unlimited

Math Unlimited
  • Author : R. Sujatha,H. N. Ramaswamy,C. S. Yogananda
  • Publisher : CRC Press
  • Release : 11 November 2011
GET THIS BOOK Math Unlimited

This collection of essays spans pure and applied mathematics. Readers interested in mathematical research and historical aspects of mathematics will appreciate the enlightening content of the material. Highlighting the pervasive nature of mathematics today in a host of different areas, the book also covers the spread of mathematical ideas and techniques in areas ranging from computer science to physics to biology.

Neuroscience

Neuroscience
  • Author : Alwyn Scott
  • Publisher : Springer Science & Business Media
  • Release : 14 December 2007
GET THIS BOOK Neuroscience

This book will be of interest to anyone who wishes to know what role mathematics can play in attempting to comprehend the dynamics of the human brain. It also aims to serve as a general introduction to neuromathematics. The book gives the reader a qualitative understanding and working knowledge of useful mathematical applications to the field of neuroscience. The book is readable by those who have little knowledge of mathematics for neuroscience but are committed to begin acquiring such knowledge.

Mathematical Concepts and Methods in Modern Biology

Mathematical Concepts and Methods in Modern Biology
  • Author : Raina Robeva,Terrell Hodge
  • Publisher : Academic Press
  • Release : 26 February 2013
GET THIS BOOK Mathematical Concepts and Methods in Modern Biology

Mathematical Concepts and Methods in Modern Biology offers a quantitative framework for analyzing, predicting, and modulating the behavior of complex biological systems. The book presents important mathematical concepts, methods and tools in the context of essential questions raised in modern biology. Designed around the principles of project-based learning and problem-solving, the book considers biological topics such as neuronal networks, plant population growth, metabolic pathways, and phylogenetic tree reconstruction. The mathematical modeling tools brought to bear on these topics include Boolean

Stochastic Methods in Neuroscience

Stochastic Methods in Neuroscience
  • Author : Carlo Laing,Gabriel J Lord
  • Publisher : OUP Oxford
  • Release : 24 September 2009
GET THIS BOOK Stochastic Methods in Neuroscience

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

Spatial Dynamics and Pattern Formation in Biological Populations

Spatial Dynamics and Pattern Formation in Biological Populations
  • Author : Ranjit Kumar Upadhyay,Satteluri R. K. Iyengar
  • Publisher : CRC Press
  • Release : 23 February 2021
GET THIS BOOK Spatial Dynamics and Pattern Formation in Biological Populations

The book provides an introduction to deterministic (and some stochastic) modeling of spatiotemporal phenomena in ecology, epidemiology, and neural systems. A survey of the classical models in the fields with up to date applications is given. The book begins with detailed description of how spatial dynamics/diffusive processes influence the dynamics of biological populations. These processes play a key role in understanding the outbreak and spread of pandemics which help us in designing the control strategies from the public health