Mathematical Foundations of Neuroscience

Mathematical Foundations of Neuroscience PDF Author: G. Bard Ermentrout
Publisher: Springer Science & Business Media
ISBN: 0387877088
Category : Mathematics
Languages : en
Pages : 434

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Book Description
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.

Computational Neuroscience

Computational Neuroscience PDF Author: Erik De Schutter
Publisher: CRC Press
ISBN: 1420039296
Category : Mathematics
Languages : en
Pages : 368

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Book Description
Designed primarily as an introduction to realistic modeling methods, Computational Neuroscience: Realistic Modeling for Experimentalists focuses on methodological approaches, selecting appropriate methods, and identifying potential pitfalls. The author addresses varying levels of complexity, from molecular interactions within single neurons to the

Mathematics for Neuroscientists

Mathematics for Neuroscientists PDF Author: Fabrizio Gabbiani
Publisher: Academic Press
ISBN: 0128019069
Category : Science
Languages : en
Pages : 628

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Book Description
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 on extracellular potentials, motion detection and neurovascular coupling Revised selection of exercises with solutions More than 200 Matlab scripts reproducing the figures as well as a selection of equivalent Python scripts

Foundations and Methods from Mathematics to Neuroscience

Foundations and Methods from Mathematics to Neuroscience PDF Author: Colleen Crangle
Publisher: Center for the Study of Language and Information Publica Tion
ISBN: 9781575867441
Category : Logic, Symbolic and mathematical
Languages : en
Pages : 0

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Book Description
During his long and continuing scholarly career, Patrick Suppes contributed significantly both to the sciences and to their philosophies. The volume consists of papers by an international group of Suppes colleagues, collaborators, and students in many of the areas of his expertise, building on or adding to his insights. Michael Friedman offers an overview of Suppes accomplishments and of his unique perspective on the relation between science and philosophy. Paul Humphreys, Stephen Hartmann, and Tom Ryckman present essays in the philosophy of physics. Jens-Erik Fenstad, Harvey Friedman, and Jaako Hintikka consider problems in the foundations of mathematics, while the late Duncan Luce, Jean-Claude Falmagne, Brian Skyrms, and Hannes Leitgeb have contributed essays in theory of measurement, decision theory and probability. Foundations of economics and political theory are addressed by Adolfo Garcia de la Sienra, Russell Hardin, and Kenneth Arrow. Psychology, language, and philosophy of language are addressed by Elizabeth Loftus, Anne Fagot-Largeault, Willem Levelt, Dagfinn Follesdal, and Marcos Perreau-Guimares and some of Suppes most recent research in neurobiology is addressed in essays by Colleen Crangle, Acadio de Barros and Claudio Carvalhes. Finally Nancy Cartwright and Alexandre Marcelles consider the alignment (or misalignment) of method and policy. Each of the essays is accompanied by a response from Suppes."

Fundamentals of Computational Neuroscience

Fundamentals of Computational Neuroscience PDF Author: Thomas Trappenberg
Publisher: Oxford University Press
ISBN: 0199568413
Category : Mathematics
Languages : en
Pages : 417

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Book Description
The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the first edition. Completely redesigned and revised, it introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain.

An Introduction to Modeling Neuronal Dynamics

An Introduction to Modeling Neuronal Dynamics PDF Author: Christoph Börgers
Publisher: Springer
ISBN: 3319511718
Category : Mathematics
Languages : en
Pages : 457

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Book Description
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 in physics is assumed, and none in biology. Topics include models of individual nerve cells and their dynamics, models of networks of neurons coupled by synapses and gap junctions, origins and functions of population rhythms in neuronal networks, and models of synaptic plasticity. An extensive online collection of Matlab programs generating the figures accompanies the book.

Philosophical Foundations of Neuroscience

Philosophical Foundations of Neuroscience PDF Author: M. R. Bennett
Publisher: Wiley-Blackwell
ISBN: 9781405108553
Category : Philosophy
Languages : en
Pages : 461

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Book Description
Writing from a scientifically and philosophically informed perspective, the authors provide a critical overview of the conceptual difficulties encountered in many current neuroscientific and psychological theories.

Learning and Computational Neuroscience

Learning and Computational Neuroscience PDF Author: Michael R. Gabriel
Publisher: Mit Press
ISBN: 9780262071024
Category : Apprentissage
Languages : en
Pages : 613

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Book Description
"Learning and Computational Neuroscience" presents recent advances in understanding the brain processes underlying learning and memory, including neural systems analyses of dynamic circuit interactions in the brain and computational models capable of describing simple forms of learning and performance. Its principal aim is to show how each approach is related to and benefits the other, providing a powerful strategy for understanding cognitive processes.Michael Gabriel is Professor of Psychology at the University of Illinois. John Moore is Professor of Psychology and Associate Professor of Computer and Information Science at the University of Massachusetts at Amherst.Contributors: Michael Gabriel and John Moore. Joseph E. LeDoux, Bruce S. Kapp, Amy Wilson, Jeffrey P. Pascoe, William Supple, Paul J. Whalen, Norman W. Weinberger, John H. Ashe, Raju Metherate, David M. Diamond, Jon S. Bakin, J. Michael Cassady. Nestor A. Schmajuk. Malcolm W. Brown. Theodore W. Berger, German Barri onuevo, Steven P. Levitan, Donald N. Krieger, Robert J. H. Sclabassi. Neil E. Berthier, Diana E. J. Blazis. E. James Kehoe. John E. Desmond. A. Harry Klopf, James S. Morgan. Richard S. Sutton, Andrew G. Barto. Christopher J. C. H. Watkins.

Spikes, Decisions, and Actions

Spikes, Decisions, and Actions PDF Author: Hugh Reid Wilson
Publisher:
ISBN: 9780198524304
Category : Medical
Languages : en
Pages : 307

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Book Description
The nervous system of higher animals is very complex and highly nonlinear. among its many capabilities are making decisions and carrying out complex motor actions such as swimming. Nonlinear dynamical modelling can be used to understand and explain neural phenomena at many different levels, including - ion-currents and action potentials; short - and long - term memory; visual hallucinations; neural synchronization; motor control This book explores the mathematical principles by which brains generate spikes, make decisions, store memories, and control actions. It assumes a basic knowledge of calculus and develops the dynamical foundations of neuroscience using problem sets and computer simulations on the accompanying PC and Mac compatible MatLab disk.

Tutorials in Mathematical Biosciences I

Tutorials in Mathematical Biosciences I PDF Author: Alla Borisyuk
Publisher: Springer
ISBN: 3540315446
Category : Mathematics
Languages : en
Pages : 170

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Book Description
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 connections. Chapter 4 specializes to one particular neuronal system, namely, the auditory system. It includes a self-contained introduction, from the anatomy and physiology of the inner ear to the neuronal network that connects the hair cells to the cortex, and describes various models of subsystems.