Modeling In The Neurosciences

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Modeling in the Neurosciences

Author : G N Reeke
Publisher : CRC Press
ISBN 13 : 9780367393175
Total Pages : 736 pages
Book Rating : 4.3/5 (931 download)

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Book Synopsis Modeling in the Neurosciences by : G N Reeke

Download or read book Modeling in the Neurosciences written by G N Reeke and published by CRC Press. This book was released on 2019-08-30 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational models of neural networks have proven insufficient to accurately model brain function, mainly as a result of simplifications that ignore the physical reality of neuronal structure in favor of mathematically tractable algorithms and rules. Even the more biologically based "integrate and fire" and "compartmental" styles of modeling suffer from oversimplification in the former case and excessive discretization in the second. This book introduces an integrative approach to modeling neurons and neuronal circuits that retains the integrity of the biological units at all hierarchical levels. With contributions from more than 40 renowned experts, Modeling in the Neurosciences, Second Edition is essential for those interested in constructing more structured and integrative models with greater biological insight. Focusing on new mathematical and computer models, techniques, and methods, this book represents a cohesive and comprehensive treatment of various aspects of the neurosciences from the molecular to the network level. Many state-of-the-art examples illustrate how mathematical and computer modeling can contribute to the understanding of mechanisms and systems in the neurosciences. Each chapter also includes suggestions of possible refinements for future modeling in this rapidly changing and expanding field. This book will benefit and inspire the advanced modeler, and will give the beginner sufficient confidence to model a wide selection of neuronal systems at the molecular, cellular, and network levels.

Principles of Computational Modelling in Neuroscience

Author : David Sterratt
Publisher : Cambridge University Press
ISBN 13 : 1108483143
Total Pages : 553 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Principles of Computational Modelling in Neuroscience by : David Sterratt

Download or read book Principles of Computational Modelling in Neuroscience written by David Sterratt and published by Cambridge University Press. This book was released on 2023-10-05 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.

Modeling in the Neurosciences

Author : G. N. Reeke
Publisher : CRC Press
ISBN 13 : 0203390970
Total Pages : 736 pages
Book Rating : 4.2/5 (33 download)

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Book Synopsis Modeling in the Neurosciences by : G. N. Reeke

An Introduction to Modeling Neuronal Dynamics

Author : Christoph Börgers
Publisher : Springer
ISBN 13 : 3319511718
Total Pages : 457 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis An Introduction to Modeling Neuronal Dynamics by : Christoph Börgers

Download or read book An Introduction to Modeling Neuronal Dynamics written by Christoph Börgers and published by Springer. This book was released on 2017-04-17 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Computational Neuroscience Models of the Basal Ganglia

Author : V. Srinivasa Chakravarthy
Publisher : Springer
ISBN 13 : 9811084947
Total Pages : 296 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Computational Neuroscience Models of the Basal Ganglia by : V. Srinivasa Chakravarthy

Download or read book Computational Neuroscience Models of the Basal Ganglia written by V. Srinivasa Chakravarthy and published by Springer. This book was released on 2018-03-21 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a compendium of the aforementioned subclass of models of Basal Ganglia, which presents some the key existent theories of Basal Ganglia function. The book presents computational models of basal ganglia-related disorders, including Parkinson’s disease, schizophrenia, and addiction. Importantly, it highlights the applications of understanding the role of the basal ganglia to treat neurological and psychiatric disorders. The purpose of the present book is to amend and expand on James Houk’s book (MIT press; ASIN: B010BF4U9K) by providing a comprehensive overview on computational models of the basal ganglia. This book caters to researchers and academics from the area of computational cognitive neuroscience.

An Introduction to Model-Based Cognitive Neuroscience

Author : Birte U. Forstmann
Publisher : Springer Nature
ISBN 13 : 3031452712
Total Pages : 384 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis An Introduction to Model-Based Cognitive Neuroscience by : Birte U. Forstmann

Download or read book An Introduction to Model-Based Cognitive Neuroscience written by Birte U. Forstmann and published by Springer Nature. This book was released on with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Fundamentals of Neural Network Modeling

Author : Randolph W. Parks
Publisher : MIT Press
ISBN 13 : 9780262161756
Total Pages : 450 pages
Book Rating : 4.1/5 (617 download)

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Book Synopsis Fundamentals of Neural Network Modeling by : Randolph W. Parks

Download or read book Fundamentals of Neural Network Modeling written by Randolph W. Parks and published by MIT Press. This book was released on 1998 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. Over the past few years, computer modeling has become more prevalent in the clinical sciences as an alternative to traditional symbol-processing models. This book provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. It is intended to make the neural network approach accessible to practicing neuropsychologists, psychologists, neurologists, and psychiatrists. It will also be a useful resource for computer scientists, mathematicians, and interdisciplinary cognitive neuroscientists. The editors (in their introduction) and contributors explain the basic concepts behind modeling and avoid the use of high-level mathematics. The book is divided into four parts. Part I provides an extensive but basic overview of neural network modeling, including its history, present, and future trends. It also includes chapters on attention, memory, and primate studies. Part II discusses neural network models of behavioral states such as alcohol dependence, learned helplessness, depression, and waking and sleeping. Part III presents neural network models of neuropsychological tests such as the Wisconsin Card Sorting Task, the Tower of Hanoi, and the Stroop Test. Finally, part IV describes the application of neural network models to dementia: models of acetycholine and memory, verbal fluency, Parkinsons disease, and Alzheimer's disease. Contributors J. Wesson Ashford, Rajendra D. Badgaiyan, Jean P. Banquet, Yves Burnod, Nelson Butters, John Cardoso, Agnes S. Chan, Jean-Pierre Changeux, Kerry L. Coburn, Jonathan D. Cohen, Laurent Cohen, Jose L. Contreras-Vidal, Antonio R. Damasio, Hanna Damasio, Stanislas Dehaene, Martha J. Farah, Joaquin M. Fuster, Philippe Gaussier, Angelika Gissler, Dylan G. Harwood, Michael E. Hasselmo, J, Allan Hobson, Sam Leven, Daniel S. Levine, Debra L. Long, Roderick K. Mahurin, Raymond L. Ownby, Randolph W. Parks, Michael I. Posner, David P. Salmon, David Servan-Schreiber, Chantal E. Stern, Jeffrey P. Sutton, Lynette J. Tippett, Daniel Tranel, Bradley Wyble

Introduction to Dynamic Modeling of Neuro-Sensory Systems

Author : Robert B. Northrop
Publisher : CRC Press
ISBN 13 : 142004172X
Total Pages : 488 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Introduction to Dynamic Modeling of Neuro-Sensory Systems by : Robert B. Northrop

Download or read book Introduction to Dynamic Modeling of Neuro-Sensory Systems written by Robert B. Northrop and published by CRC Press. This book was released on 2000-11-27 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although neural modeling has a long history, most of the texts available on the subject are quite limited in scope, dealing primarily with the simulation of large-scale biological neural networks applicable to describing brain function. Introduction to Dynamic Modeling of Neuro-Sensory Systems presents the mathematical tools and methods that can describe and predict the dynamic behavior of single neurons, small assemblies of neurons devoted to a single tasks, as well as larger sensory arrays and their underlying neuropile. Focusing on small and medium-sized biological neural networks, the author pays particular attention to visual feature extraction, especially the compound eye visual system and the vertebrate retina. For computational efficiency, the treatment avoids molecular details of neuron function and uses the locus approach for medium-scale modeling of arrays. Rather than requiring readers to learn a dedicated simulation program, the author uses the general, nonlinear ordinary differential equation solver Simnonä for all examples and exercises. There is both art and science in setting up a computational model that can be validated from existing neurophysiological data. With clear prose, more than 200 figures and photographs, and unique focus, Introduction to Dynamic Modeling of Neuro-Sensory Systems develops the science, nurtures the art, and builds the foundation for more advanced work in neuroscience and the rapidly emerging field of neuroengineering.

Time Series Modeling of Neuroscience Data

Author : Tohru Ozaki
Publisher : CRC Press
ISBN 13 : 1420094610
Total Pages : 574 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Time Series Modeling of Neuroscience Data by : Tohru Ozaki

Download or read book Time Series Modeling of Neuroscience Data written by Tohru Ozaki and published by CRC Press. This book was released on 2012-01-26 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in brain science measurement technology have given researchers access to very large-scale time series data such as EEG/MEG data (20 to 100 dimensional) and fMRI (140,000 dimensional) data. To analyze such massive data, efficient computational and statistical methods are required. Time Series Modeling of Neuroscience Data shows how to efficiently analyze neuroscience data by the Wiener-Kalman-Akaike approach, in which dynamic models of all kinds, such as linear/nonlinear differential equation models and time series models, are used for whitening the temporally dependent time series in the framework of linear/nonlinear state space models. Using as little mathematics as possible, this book explores some of its basic concepts and their derivatives as useful tools for time series analysis. Unique features include: A statistical identification method of highly nonlinear dynamical systems such as the Hodgkin-Huxley model, Lorenz chaos model, Zetterberg Model, and more Methods and applications for Dynamic Causality Analysis developed by Wiener, Granger, and Akaike A state space modeling method for dynamicization of solutions for the Inverse Problems A heteroscedastic state space modeling method for dynamic non-stationary signal decomposition for applications to signal detection problems in EEG data analysis An innovation-based method for the characterization of nonlinear and/or non-Gaussian time series An innovation-based method for spatial time series modeling for fMRI data analysis The main point of interest in this book is to show that the same data can be treated using both a dynamical system and time series approach so that the neural and physiological information can be extracted more efficiently. Of course, time series modeling is valid not only in neuroscience data analysis but also in many other sciences and engineering fields where the statistical inference from the observed time series data plays an important role.

Modeling in the Neurosciences

Author : R.R. Poznanski
Publisher : Routledge
ISBN 13 : 1351430971
Total Pages : 528 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Modeling in the Neurosciences by : R.R. Poznanski

Download or read book Modeling in the Neurosciences written by R.R. Poznanski and published by Routledge. This book was released on 2019-01-22 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: With contributions from more than 40 renowned experts, Modeling in the Neurosciences: From Ionic Channels to Neural Networks is essential for those interested in neuronal modeling and quantitative neiroscience. Focusing on new mathematical and computer models, techniques and methods, this monograph represents a cohesive and comprehensive treatment

Dynamical Systems in Neuroscience

Author : Eugene M. Izhikevich
Publisher : MIT Press
ISBN 13 : 0262514206
Total Pages : 459 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Dynamical Systems in Neuroscience by : Eugene M. Izhikevich

Download or read book Dynamical Systems in Neuroscience written by Eugene M. Izhikevich and published by MIT Press. This book was released on 2010-01-22 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition. In order to model neuronal behavior or to interpret the results of modeling studies, neuroscientists must call upon methods of nonlinear dynamics. This book offers an introduction to nonlinear dynamical systems theory for researchers and graduate students in neuroscience. It also provides an overview of neuroscience for mathematicians who want to learn the basic facts of electrophysiology. Dynamical Systems in Neuroscience presents a systematic study of the relationship of electrophysiology, nonlinear dynamics, and computational properties of neurons. It emphasizes that information processing in the brain depends not only on the electrophysiological properties of neurons but also on their dynamical properties. The book introduces dynamical systems, starting with one- and two-dimensional Hodgkin-Huxley-type models and continuing to a description of bursting systems. Each chapter proceeds from the simple to the complex, and provides sample problems at the end. The book explains all necessary mathematical concepts using geometrical intuition; it includes many figures and few equations, making it especially suitable for non-mathematicians. Each concept is presented in terms of both neuroscience and mathematics, providing a link between the two disciplines. Nonlinear dynamical systems theory is at the core of computational neuroscience research, but it is not a standard part of the graduate neuroscience curriculum—or taught by math or physics department in a way that is suitable for students of biology. This book offers neuroscience students and researchers a comprehensive account of concepts and methods increasingly used in computational neuroscience. An additional chapter on synchronization, with more advanced material, can be found at the author's website, www.izhikevich.com.

Computational Neuroscience

Author : Erik De Schutter
Publisher : CRC Press
ISBN 13 : 1420039296
Total Pages : 368 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Computational Neuroscience by : Erik De Schutter

Download or read book Computational Neuroscience written by Erik De Schutter and published by CRC Press. This book was released on 2000-11-22 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Dynamic Neuroscience

Author : Zhe Chen
Publisher : Springer
ISBN 13 : 3319719769
Total Pages : 327 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Dynamic Neuroscience by : Zhe Chen

Download or read book Dynamic Neuroscience written by Zhe Chen and published by Springer. This book was released on 2017-12-27 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how to develop efficient quantitative methods to characterize neural data and extra information that reveals underlying dynamics and neurophysiological mechanisms. Written by active experts in the field, it contains an exchange of innovative ideas among researchers at both computational and experimental ends, as well as those at the interface. Authors discuss research challenges and new directions in emerging areas with two goals in mind: to collect recent advances in statistics, signal processing, modeling, and control methods in neuroscience; and to welcome and foster innovative or cross-disciplinary ideas along this line of research and discuss important research issues in neural data analysis. Making use of both tutorial and review materials, this book is written for neural, electrical, and biomedical engineers; computational neuroscientists; statisticians; computer scientists; and clinical engineers.

Modeling in the Neurosciences

Author : G. N. Reeke
Publisher : CRC Press
ISBN 13 : 9781134333356
Total Pages : 736 pages
Book Rating : 4.3/5 (333 download)

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Book Synopsis Modeling in the Neurosciences by : G. N. Reeke

Download or read book Modeling in the Neurosciences written by G. N. Reeke and published by CRC Press. This book was released on 2005-03-29 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational models of neural networks have proven insufficient to accurately model brain function, mainly as a result of simplifications that ignore the physical reality of neuronal structure in favor of mathematically tractable algorithms and rules. Even the more biologically based "integrate and fire" and "compartmental" styles of modeling suffer from oversimplification in the former case and excessive discretization in the second. This book introduces an integrative approach to modeling neurons and neuronal circuits that retains the integrity of the biological units at all hierarchical levels. With contributions from more than 40 renowned experts, Modeling in the Neurosciences, Second Edition is essential for those interested in constructing more structured and integrative models with greater biological insight. Focusing on new mathematical and computer models, techniques, and methods, this book represents a cohesive and comprehensive treatment of various aspects of the neurosciences from the molecular to the network level. Many state-of-the-art examples illustrate how mathematical and computer modeling can contribute to the understanding of mechanisms and systems in the neurosciences. Each chapter also includes suggestions of possible refinements for future modeling in this rapidly changing and expanding field. This book will benefit and inspire the advanced modeler, and will give the beginner sufficient confidence to model a wide selection of neuronal systems at the molecular, cellular, and network levels.

Methods in Neuronal Modeling

Author : Christof Koch
Publisher : MIT Press
ISBN 13 : 9780262112314
Total Pages : 700 pages
Book Rating : 4.1/5 (123 download)

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Book Synopsis Methods in Neuronal Modeling by : Christof Koch

Download or read book Methods in Neuronal Modeling written by Christof Koch and published by MIT Press. This book was released on 1998 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kinetic Models of Synaptic Transmission / Alain Destexhe, Zachary F. Mainen, Terrence J. Sejnowski / - Cable Theory for Dendritic Neurons / Wilfrid Rall, Hagai Agmon-Snir / - Compartmental Models of Complex Neurons / Idan Segev, Robert E. Burke / - Multiple Channels and Calcium Dynamics / Walter M. Yamada, Christof Koch, Paul R. Adams / - Modeling Active Dendritic Processes in Pyramidal Neurons / Zachary F. Mainen, Terrence J. Sejnowski / - Calcium Dynamics in Large Neuronal Models / Erik De Schutter, Paul Smolen / - Analysis of Neural Excitability and Oscillations / John Rinzel, Bard Ermentrout / - Design and Fabrication of Analog VLSI Neurons / Rodney Douglas, Misha Mahowald / - Principles of Spike Train Analysis / Fabrizio Gabbiani, Christof Koch / - Modeling Small Networks / Larry Abbott, Eve Marder / - Spatial and Temporal Processing in Central Auditory Networks / Shihab Shamma / - Simulating Large Networks of Neurons / Alexander D. Protopapas, Michael Vanier, James M. Bower / ...

Neuronal Dynamics

Author : Wulfram Gerstner
Publisher : Cambridge University Press
ISBN 13 : 1107060834
Total Pages : 591 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Neuronal Dynamics by : Wulfram Gerstner

Download or read book Neuronal Dynamics written by Wulfram Gerstner and published by Cambridge University Press. This book was released on 2014-07-24 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.

Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications

Author : Alonso, Eduardo
Publisher : IGI Global
ISBN 13 : 1609600231
Total Pages : 396 pages
Book Rating : 4.6/5 (96 download)

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Book Synopsis Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications by : Alonso, Eduardo

Download or read book Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications written by Alonso, Eduardo and published by IGI Global. This book was released on 2010-11-30 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book argues that computational models in behavioral neuroscience must be taken with caution, and advocates for the study of mathematical models of existing theories as complementary to neuro-psychological models and computational models"--