Mathematical Neuroscience

Written By Stanislaw Brzychczy
Mathematical Neuroscience
  • Publsiher : Academic Press
  • Release : 16 August 2013
  • ISBN : 0124104827
  • Pages : 208 pages
  • Rating : /5 from reviews
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Download or read book entitled Mathematical Neuroscience by author: Stanislaw Brzychczy which was release on 16 August 2013 and published by Academic Press with total page 208 pages . This book available in PDF, EPUB and Kindle Format. 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 reflect an integrative approach. This book examines the solvability of infinite systems of reaction diffusion type equations in partially ordered abstract spaces. It considers various methods and techniques of nonlinear analysis, including comparison theorems, monotone iterative techniques, a truncation method, and topological fixed point methods. Infinite systems of such equations play a crucial role in the integrative aspects of neuroscience modeling. The first focused introduction to the use of nonlinear analysis with an infinite dimensional approach to theoretical neuroscience Combines functional analysis techniques with nonlinear dynamical systems applied to the study of the brain Introduces powerful mathematical techniques to manage the dynamics and challenges of infinite systems of equations applied to neuroscience modeling

Mathematical Neuroscience

Mathematical Neuroscience
  • Author : Stanislaw Brzychczy,Roman R. Poznanski
  • Publisher : Academic Press
  • Release Date : 2013-08-16
  • Total pages : 208
  • ISBN : 0124104827
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Summary : 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 ...

Mathematical Foundations of Neuroscience

Mathematical Foundations of Neuroscience
  • Author : G. Bard Ermentrout,David H. Terman
  • Publisher : Springer Science & Business Media
  • Release Date : 2010-07-01
  • Total pages : 422
  • ISBN : 0124104827
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Summary : 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 ...

Mathematics for Neuroscientists

Mathematics for Neuroscientists
  • Author : Fabrizio Gabbiani,Steven James Cox
  • Publisher : Academic Press
  • Release Date : 2017-03-21
  • Total pages : 628
  • ISBN : 0124104827
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Summary : 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 ...

Mathematical Neuroscience

Mathematical Neuroscience
  • Author : Anonim
  • Publisher : Unknown
  • Release Date : 2005
  • Total pages : 170
  • ISBN : 0124104827
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Summary : Read online Mathematical Neuroscience written by , published by which was released on 2005. Download full Mathematical Neuroscience Books now! Available in PDF, ePub and Kindle....

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 Date : 2005-02-18
  • Total pages : 170
  • ISBN : 0124104827
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Summary : 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 ...

Neuroscience

Neuroscience
  • Author : Alwyn Scott
  • Publisher : Springer Science & Business Media
  • Release Date : 2007-12-14
  • Total pages : 352
  • ISBN : 0124104827
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Summary : 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 ...

Mathematical and Theoretical Neuroscience

Mathematical and Theoretical Neuroscience
  • Author : Giovanni Naldi,Thierry Nieus
  • Publisher : Springer
  • Release Date : 2018-03-20
  • Total pages : 253
  • ISBN : 0124104827
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Summary : 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 ...

Tutorials in Mathematical Biosciences I

Tutorials in Mathematical Biosciences I
  • Author : Alla Borisyuk,G. Bard Ermentrout,Avner Friedman,David H. Terman
  • Publisher : Springer
  • Release Date : 2009-09-02
  • Total pages : 170
  • ISBN : 0124104827
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Summary : 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 ...

Mathematical Foundations of Neuroscience

Mathematical Foundations of Neuroscience
  • Author : G. Bard Ermentrout,David H. Terman
  • Publisher : Springer Science & Business Media
  • Release Date : 2010-07-08
  • Total pages : 422
  • ISBN : 0124104827
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Summary : Arising from several courses taught by the authors, this book provides a needed overview illustrating how dynamical systems and computational analysis have been used in understanding the types of models that come out of neuroscience....

From Computer to Brain

From Computer to Brain
  • Author : William W. Lytton
  • Publisher : Springer Science & Business Media
  • Release Date : 2007-05-08
  • Total pages : 364
  • ISBN : 0124104827
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Summary : Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. ...

An Introduction to Modeling Neuronal Dynamics

An Introduction to Modeling Neuronal Dynamics
  • Author : Christoph Börgers
  • Publisher : Springer
  • Release Date : 2017-04-17
  • Total pages : 457
  • ISBN : 0124104827
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Summary : This book is intended as a text for a one-semester course on Mathematical and Computational Neuroscience for upper-level undergraduate and beginning graduate students of mathematics, the natural sciences, engineering, or computer science. An undergraduate introduction to differential equations is more than enough mathematical background. Only a slim, high school-level background ...

Stochastic Methods in Neuroscience

Stochastic Methods in Neuroscience
  • Author : Carlo Laing,Gabriel J Lord
  • Publisher : OUP Oxford
  • Release Date : 2009-09-24
  • Total pages : 396
  • ISBN : 0124104827
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Summary : 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 ...

Neuroscience of Mathematical Cognitive Development

Neuroscience of Mathematical Cognitive Development
  • Author : Rhonda Douglas Brown
  • Publisher : Springer
  • Release Date : 2018-04-13
  • Total pages : 146
  • ISBN : 0124104827
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Summary : ​This book examines the neuroscience of mathematical cognitive development from infancy into emerging adulthood, addressing both biological and environmental influences on brain development and plasticity. It begins by presenting major theoretical frameworks for designing and interpreting neuroscience studies of mathematical cognitive development, including developmental evolutionary theory, developmental systems approaches, and ...

Mathematical Foundations of Neuroscience

Mathematical Foundations of Neuroscience
  • Author : G. Bard Ermentrout,David H. Terman
  • Publisher : Springer
  • Release Date : 2010-07-08
  • Total pages : 422
  • ISBN : 0124104827
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Summary : Arising from several courses taught by the authors, this book provides a needed overview illustrating how dynamical systems and computational analysis have been used in understanding the types of models that come out of neuroscience....

Weakly Connected Neural Networks

Weakly Connected Neural Networks
  • Author : Frank C. Hoppensteadt,Eugene M. Izhikevich
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • Total pages : 402
  • ISBN : 0124104827
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Summary : Devoted to local and global analysis of weakly connected systems with applications to neurosciences, this book uses bifurcation theory and canonical models as the major tools of analysis. It presents a systematic and well motivated development of both weakly connected system theory and mathematical neuroscience, addressing bifurcations in neuron and ...