From Neuron To Cognition Via Computational Neuroscience
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From Neuron To Cognition Via Computational Neuroscience
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Author : Michael A. Arbib
language : en
Publisher: MIT Press
Release Date : 2016-11-04
From Neuron To Cognition Via Computational Neuroscience written by Michael A. Arbib and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-04 with Science categories.
A comprehensive, integrated, and accessible textbook presenting core neuroscientific topics from a computational perspective, tracing a path from cells and circuits to behavior and cognition. This textbook presents a wide range of subjects in neuroscience from a computational perspective. It offers a comprehensive, integrated introduction to core topics, using computational tools to trace a path from neurons and circuits to behavior and cognition. Moreover, the chapters show how computational neuroscience—methods for modeling the causal interactions underlying neural systems—complements empirical research in advancing the understanding of brain and behavior. The chapters—all by leaders in the field, and carefully integrated by the editors—cover such subjects as action and motor control; neuroplasticity, neuromodulation, and reinforcement learning; vision; and language—the core of human cognition. The book can be used for advanced undergraduate or graduate level courses. It presents all necessary background in neuroscience beyond basic facts about neurons and synapses and general ideas about the structure and function of the human brain. Students should be familiar with differential equations and probability theory, and be able to pick up the basics of programming in MATLAB and/or Python. Slides, exercises, and other ancillary materials are freely available online, and many of the models described in the chapters are documented in the brain operation database, BODB (which is also described in a book chapter). Contributors Michael A. Arbib, Joseph Ayers, James Bednar, Andrej Bicanski, James J. Bonaiuto, Nicolas Brunel, Jean-Marie Cabelguen, Carmen Canavier, Angelo Cangelosi, Richard P. Cooper, Carlos R. Cortes, Nathaniel Daw, Paul Dean, Peter Ford Dominey, Pierre Enel, Jean-Marc Fellous, Stefano Fusi, Wulfram Gerstner, Frank Grasso, Jacqueline A. Griego, Ziad M. Hafed, Michael E. Hasselmo, Auke Ijspeert, Stephanie Jones, Daniel Kersten, Jeremie Knuesel, Owen Lewis, William W. Lytton, Tomaso Poggio, John Porrill, Tony J. Prescott, John Rinzel, Edmund Rolls, Jonathan Rubin, Nicolas Schweighofer, Mohamed A. Sherif, Malle A. Tagamets, Paul F. M. J. Verschure, Nathan Vierling-Claasen, Xiao-Jing Wang, Christopher Williams, Ransom Winder, Alan L. Yuille
Neuronal Dynamics
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Author : Wulfram Gerstner
language : en
Publisher: Cambridge University Press
Release Date : 2014-07-24
Neuronal Dynamics written by Wulfram Gerstner and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-24 with Computers categories.
This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.
An Introductory Course In Computational Neuroscience
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Author : Paul Miller
language : en
Publisher: MIT Press
Release Date : 2018-10-02
An Introductory Course In Computational Neuroscience written by Paul Miller and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-02 with Science categories.
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.
Computational Neuroscience Theoretical Insights Into Brain Function
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Author : Paul Cisek
language : en
Publisher: Elsevier
Release Date : 2007-11-14
Computational Neuroscience Theoretical Insights Into Brain Function written by Paul Cisek and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-14 with Science categories.
Computational neuroscience is a relatively new but rapidly expanding area of research which is becoming increasingly influential in shaping the way scientists think about the brain. Computational approaches have been applied at all levels of analysis, from detailed models of single-channel function, transmembrane currents, single-cell electrical activity, and neural signaling to broad theories of sensory perception, memory, and cognition. This book provides a snapshot of this exciting new field by bringing together chapters on a diversity of topics from some of its most important contributors. This includes chapters on neural coding in single cells, in small networks, and across the entire cerebral cortex, visual processing from the retina to object recognition, neural processing of auditory, vestibular, and electromagnetic stimuli, pattern generation, voluntary movement and posture, motor learning, decision-making and cognition, and algorithms for pattern recognition. Each chapter provides a bridge between a body of data on neural function and a mathematical approach used to interpret and explain that data. These contributions demonstrate how computational approaches have become an essential tool which is integral in many aspects of brain science, from the interpretation of data to the design of new experiments, and to the growth of our understanding of neural function. • Includes contributions by some of the most influential people in the field of computational neuroscience • Demonstrates how computational approaches are being used today to interpret experimental data • Covers a wide range of topics from single neurons, to neural systems, to abstract models of learning
Introduction To Computational Neuroscience
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Author : Madison White
language : en
Publisher: Willford Press
Release Date : 2021-11-16
Introduction To Computational Neuroscience written by Madison White and has been published by Willford Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-16 with Computers categories.
The branch of neuroscience that uses theoretical analysis, mathematical models and abstractions of the brain for understanding the nervous system is known as computational neuroscience. It is involved in studying the development, structure, physiology and cognitive abilities of the nervous system. The models within this field seek to capture the essential features of the biological system at multi-spatial temporal scales. These models are used to develop hypotheses which can be tested through biological or psychological experiments. The major topics that are studied under computational neuroscience are single-neuron modeling, sensory processing, motor control, computational clinical neuroscience, cognition, discrimination and learning, memory, and synaptic plasticity. This book outlines the processes and applications of computational neuroscience in detail. The various studies that are constantly contributing towards advancing technologies and evolution of this field are examined in detail. This book will provide comprehensive knowledge to the readers.
Computational Neuroscience Of Cognition
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Author : Xiao-Jing Wang
language : en
Publisher:
Release Date : 2023
Computational Neuroscience Of Cognition written by Xiao-Jing Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Cognitive neuroscience categories.
"A synthesis of neuroscience & cognitive science across multiple levels, grounded in experimental studies of basic cognitive functions, and with a focus on mathematical modeling of the brain"--
Cognitive And Computational Neuroscience
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Author : Seyyed Abed Hosseini
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-05-30
Cognitive And Computational Neuroscience written by Seyyed Abed Hosseini and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-30 with Medical categories.
The book "Cognitive and Computational Neuroscience - Principles, Algorithms and Applications" will answer the following question and statements: System-level neural modeling: what and why? We know a lot about the brain! Need to integrate data: molecular/cellular/system levels. Complexity: need to abstract away higher-order principles. Models are tools to develop explicit theories, constrained by multiple levels (neural and behavioral). Key: models (should) make novel testable predictions on both neural and behavioral levels. Models are useful tools for guiding experiments. The hope is that the information provided in this book will trigger new researches that will help to connect basic neuroscience to clinical medicine.
Memory And The Computational Brain
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Author : C. R. Gallistel
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-09
Memory And The Computational Brain written by C. R. Gallistel and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-09 with Language Arts & Disciplines categories.
Memory and the Computational Brain offers a provocative argument that goes to the heart of neuroscience, proposing that the field can and should benefit from the recent advances of cognitive science and the development of information theory over the course of the last several decades. A provocative argument that impacts across the fields of linguistics, cognitive science, and neuroscience, suggesting new perspectives on learning mechanisms in the brain Proposes that the field of neuroscience can and should benefit from the recent advances of cognitive science and the development of information theory Suggests that the architecture of the brain is structured precisely for learning and for memory, and integrates the concept of an addressable read/write memory mechanism into the foundations of neuroscience Based on lectures in the prestigious Blackwell-Maryland Lectures in Language and Cognition, and now significantly reworked and expanded to make it ideal for students and faculty
Computational Neuroscience
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Author : Hanspeter A Mallot
language : en
Publisher: Springer
Release Date : 2013-06-05
Computational Neuroscience written by Hanspeter A Mallot and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-05 with Technology & Engineering categories.
Computational Neuroscience - A First Course provides an essential introduction to computational neuroscience and equips readers with a fundamental understanding of modeling the nervous system at the membrane, cellular, and network level. The book, which grew out of a lecture series held regularly for more than ten years to graduate students in neuroscience with backgrounds in biology, psychology and medicine, takes its readers on a journey through three fundamental domains of computational neuroscience: membrane biophysics, systems theory and artificial neural networks. The required mathematical concepts are kept as intuitive and simple as possible throughout the book, making it fully accessible to readers who are less familiar with mathematics. Overall, Computational Neuroscience - A First Course represents an essential reference guide for all neuroscientists who use computational methods in their daily work, as well as for any theoretical scientist approaching the field of computational neuroscience.
From Computer To Brain
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Author : William W. Lytton
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-08
From Computer To Brain written by William W. Lytton and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-08 with Mathematics categories.
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. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.