An Introduction to the Mathematics of Neurons PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download An Introduction to the Mathematics of Neurons PDF full book. Access full book title An Introduction to the Mathematics of Neurons by F. C. Hoppensteadt. Download full books in PDF and EPUB format.
Author: F. C. Hoppensteadt
Publisher: Cambridge University Press
ISBN: 9780521599290
Category : Mathematics
Languages : en
Pages : 236
Get Book Here
Book Description
This book describes the signal processing aspects of neural networks. It begins with a presentation of the necessary background material in electronic circuits, mathematical modeling and analysis, signal processing, and neurosciences, and then proceeds to applications. These applications include small networks of neurons, such as those used in control of warm-up and flight in moths and control of respiration during exercise in humans. Next, a theory of mnemonic surfaces is developed and studied and material on pattern formation and cellular automata is presented. Finally, large networks are studied, such as the thalamus-reticular complex circuit, believed to be involved in focusing attention, and the development of connections in the visual cortex. Additional material is also provided about nonlinear wave propagation in networks. This book will serve as an excellent text for advanced undergraduates and graduates in the physical sciences, mathematics, engineering, medicine and life sciences.
Author: F. C. Hoppensteadt
Publisher: Cambridge University Press
ISBN: 9780521599290
Category : Mathematics
Languages : en
Pages : 236
Get Book Here
Book Description
This book describes the signal processing aspects of neural networks. It begins with a presentation of the necessary background material in electronic circuits, mathematical modeling and analysis, signal processing, and neurosciences, and then proceeds to applications. These applications include small networks of neurons, such as those used in control of warm-up and flight in moths and control of respiration during exercise in humans. Next, a theory of mnemonic surfaces is developed and studied and material on pattern formation and cellular automata is presented. Finally, large networks are studied, such as the thalamus-reticular complex circuit, believed to be involved in focusing attention, and the development of connections in the visual cortex. Additional material is also provided about nonlinear wave propagation in networks. This book will serve as an excellent text for advanced undergraduates and graduates in the physical sciences, mathematics, engineering, medicine and life sciences.
Author: Fabrizio Gabbiani
Publisher: Academic Press
ISBN: 0128019069
Category : Mathematics
Languages : en
Pages : 630
Get Book Here
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
Author: Christoph Börgers
Publisher: Springer
ISBN: 3319511718
Category : Mathematics
Languages : en
Pages : 445
Get Book Here
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.
Author: Nicholas T. Carnevale
Publisher: Cambridge University Press
ISBN: 1139447831
Category : Medical
Languages : en
Pages : 399
Get Book Here
Book Description
The authoritative reference on NEURON, the simulation environment for modeling biological neurons and neural networks that enjoys wide use in the experimental and computational neuroscience communities. This book shows how to use NEURON to construct and apply empirically based models. Written primarily for neuroscience investigators, teachers, and students, it assumes no previous knowledge of computer programming or numerical methods. Readers with a background in the physical sciences or mathematics, who have some knowledge about brain cells and circuits and are interested in computational modeling, will also find it helpful. The NEURON Book covers material that ranges from the inner workings of this program, to practical considerations involved in specifying the anatomical and biophysical properties that are to be represented in models. It uses a problem-solving approach, with many working examples that readers can try for themselves.
Author: Kevin Gurney
Publisher: CRC Press
ISBN: 1482286998
Category : Computers
Languages : en
Pages : 148
Get Book Here
Book Description
Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.
Author: Paul Miller
Publisher: MIT Press
ISBN: 0262347563
Category : Science
Languages : en
Pages : 405
Get Book Here
Book Description
A textbook for students with limited background in mathematics and computer coding, emphasizing computer tutorials that guide readers in producing models of neural behavior. This introductory text teaches students to understand, simulate, and analyze the complex behaviors of individual neurons and brain circuits. It is built around computer tutorials that guide students in producing models of neural behavior, with the associated Matlab code freely available online. From these models students learn how individual neurons function and how, when connected, neurons cooperate in a circuit. The book demonstrates through simulated models how oscillations, multistability, post-stimulus rebounds, and chaos can arise within either single neurons or circuits, and it explores their roles in the brain. The book first presents essential background in neuroscience, physics, mathematics, and Matlab, with explanations illustrated by many example problems. Subsequent chapters cover the neuron and spike production; single spike trains and the underlying cognitive processes; conductance-based models; the simulation of synaptic connections; firing-rate models of large-scale circuit operation; dynamical systems and their components; synaptic plasticity; and techniques for analysis of neuron population datasets, including principal components analysis, hidden Markov modeling, and Bayesian decoding. Accessible to undergraduates in life sciences with limited background in mathematics and computer coding, the book can be used in a “flipped” or “inverted” teaching approach, with class time devoted to hands-on work on the computer tutorials. It can also be a resource for graduate students in the life sciences who wish to gain computing skills and a deeper knowledge of neural function and neural circuits.
Author: Wulfram Gerstner
Publisher: Cambridge University Press
ISBN: 9780521890793
Category : Computers
Languages : en
Pages : 498
Get Book Here
Book Description
Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.
Author: Hoppensteadt
Publisher: Cambridge University Press
ISBN: 9780521305662
Category : Mathematics
Languages : en
Pages : 192
Get Book Here
Book Description
Neurons, or nerve cells, are basic timers in our bodies; they also play a central role in storing and processing information in our brains. This book introduces neuron physiology and some mathematical methods that can help us to understand how neurons work. The author's aim is to uncover frequency-response properties of neurons and to show that neural networks can support stable patterns of synchronized firing. He does this using a novel electrical circuit model of a neuron, called VCON, which shares many features with the Hodgkin-Huxley model, though it is much simpler to study. This makes the book suitable for advanced undergraduate or new graduate students studying mathematical biology. Indeed the book grew from such a course taught at the University of Utah. The only prerequisites are basic calculus, differential equations and matrix algebra. Problems (some with solutions) are provided at the end of each chapter; they range from simple illustrative exercises to more challenging extensions of the text. Some projects, often involving microcomputers, are also suggested.
Author: Wulfram Gerstner
Publisher: Cambridge University Press
ISBN: 1107060834
Category : Computers
Languages : en
Pages : 591
Get Book Here
Book Description
This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.
Author: Giovanni Naldi
Publisher: Springer
ISBN: 3319682970
Category : Mathematics
Languages : en
Pages : 255
Get Book Here
Book Description
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.
