Neural Codes And Distributed Representations

Author : L. F. Abbott
Publisher : MIT Press
ISBN 13 : 9780262511001
Total Pages : 378 pages
Book Rating : 4.02/5 ( download)

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Download or read book Neural Codes and Distributed Representations written by L. F. Abbott and published by MIT Press. This book was released on 1999 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. The present volume focuses on neural codes and representations, topics of broad interest to neuroscientists and modelers. The topics addressed are: how neurons encode information through action potential firing patterns, how populations of neurons represent information, and how individual neurons use dendritic processing and biophysical properties of synapses to decode spike trains. The papers encompass a wide range of levels of investigation, from dendrites and neurons to networks and systems.

Author : Asim Roy
Publisher : Frontiers Media SA
ISBN 13 : 2889455963
Total Pages : 147 pages
Book Rating : 4.66/5 ( download)

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Download or read book Representation in the Brain written by Asim Roy and published by Frontiers Media SA. This book was released on 2018-09-28 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook contains ten articles on the topic of representation of abstract concepts, both simple and complex, at the neural level in the brain. Seven of the articles directly address the main competing theories of mental representation – localist and distributed. Four of these articles argue – either on a theoretical basis or with neurophysiological evidence – that abstract concepts, simple or complex, exist (have to exist) at either the single cell level or in an exclusive neural cell assembly. There are three other papers that argue for sparse distributed representation (population coding) of abstract concepts. There are two other papers that discuss neural implementation of symbolic models. The remaining paper deals with learning of motor skills from imagery versus actual execution. A summary of these papers is provided in the Editorial.

Author : Nikolaus Kriegeskorte
Publisher : MIT Press
ISBN 13 : 0262016249
Total Pages : 659 pages
Book Rating : 4.47/5 ( download)

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Download or read book Visual Population Codes written by Nikolaus Kriegeskorte and published by MIT Press. This book was released on 2012 with total page 659 pages. Available in PDF, EPUB and Kindle. Book excerpt: How visual content is represented in neuronal population codes and how to analyze such codes with multivariate techniques. Vision is a massively parallel computational process, in which the retinal image is transformed over a sequence of stages so as to emphasize behaviorally relevant information (such as object category and identity) and deemphasize other information (such as viewpoint and lighting). The processes behind vision operate by concurrent computation and message passing among neurons within a visual area and between different areas. The theoretical concept of "population code" encapsulates the idea that visual content is represented at each stage by the pattern of activity across the local population of neurons. Understanding visual population codes ultimately requires multichannel measurement and multivariate analysis of activity patterns. Over the past decade, the multivariate approach has gained significant momentum in vision research. Functional imaging and cell recording measure brain activity in fundamentally different ways, but they now use similar theoretical concepts and mathematical tools in their modeling and analyses. With a focus on the ventral processing stream thought to underlie object recognition, this book presents recent advances in our understanding of visual population codes, novel multivariate pattern-information analysis techniques, and the beginnings of a unified perspective for cell recording and functional imaging. It serves as an introduction, overview, and reference for scientists and students across disciplines who are interested in human and primate vision and, more generally, in understanding how the brain represents and processes information.

Author : Michael A. Arbib
Publisher : MIT Press
ISBN 13 : 0262011972
Total Pages : 1328 pages
Book Rating : 4.76/5 ( download)

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Download or read book The Handbook of Brain Theory and Neural Networks written by Michael A. Arbib and published by MIT Press. This book was released on 2003 with total page 1328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).

Author : Pentti Kanerva
Publisher : MIT Press
ISBN 13 : 9780262111324
Total Pages : 194 pages
Book Rating : 4.22/5 ( download)

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Download or read book Sparse Distributed Memory written by Pentti Kanerva and published by MIT Press. This book was released on 1988 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motivated by the remarkable fluidity of memory the way in which items are pulled spontaneously and effortlessly from our memory by vague similarities to what is currently occupying our attention "Sparse Distributed Memory "presents a mathematically elegant theory of human long term memory.The book, which is self contained, begins with background material from mathematics, computers, and neurophysiology; this is followed by a step by step development of the memory model. The concluding chapter describes an autonomous system that builds from experience an internal model of the world and bases its operation on that internal model. Close attention is paid to the engineering of the memory, including comparisons to ordinary computer memories."Sparse Distributed Memory "provides an overall perspective on neural systems. The model it describes can aid in understanding human memory and learning, and a system based on it sheds light on outstanding problems in philosophy and artificial intelligence. Applications of the memory are expected to be found in the creation of adaptive systems for signal processing, speech, vision, motor control, and (in general) robots. Perhaps the most exciting aspect of the memory, in its implications for research in neural networks, is that its realization with neuronlike components resembles the cortex of the cerebellum.Pentti Kanerva is a scientist at the Research Institute for Advanced Computer Science at the NASA Ames Research Center and a visiting scholar at the Stanford Center for the Study of Language and Information. A Bradford Book.

Author : Elliot Murphy
Publisher : Cambridge University Press
ISBN 13 : 1108836313
Total Pages : 337 pages
Book Rating : 4.19/5 ( download)

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Download or read book The Oscillatory Nature of Language written by Elliot Murphy and published by Cambridge University Press. This book was released on 2020-11-05 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develops a theory of how language is processed in the brain and provides a state-of-the-art review of current neuroscientific debates.

Author : Rodrigo Quian Quiroga
Publisher : CRC Press
ISBN 13 : 1439853304
Total Pages : 643 pages
Book Rating : 4.06/5 ( download)

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Download or read book Principles of Neural Coding written by Rodrigo Quian Quiroga and published by CRC Press. This book was released on 2013-05-06 with total page 643 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding how populations of neurons encode information is the challenge faced by researchers in the field of neural coding. Focusing on the many mysteries and marvels of the mind has prompted a prominent team of experts in the field to put their heads together and fire up a book on the subject. Simply titled Principles of Neural Coding, this book covers the complexities of this discipline. It centers on some of the major developments in this area and presents a complete assessment of how neurons in the brain encode information. The book collaborators contribute various chapters that describe results in different systems (visual, auditory, somatosensory perception, etc.) and different species (monkeys, rats, humans, etc). Concentrating on the recording and analysis of the firing of single and multiple neurons, and the analysis and recording of other integrative measures of network activity and network states—such as local field potentials or current source densities—is the basis of the introductory chapters. Provides a comprehensive and interdisciplinary approach Describes topics of interest to a wide range of researchers The book then moves forward with the description of the principles of neural coding for different functions and in different species and concludes with theoretical and modeling works describing how information processing functions are implemented. The text not only contains the most important experimental findings, but gives an overview of the main methodological aspects for studying neural coding. In addition, the book describes alternative approaches based on simulations with neural networks and in silico modeling in this highly interdisciplinary topic. It can serve as an important reference to students and professionals.

Author : Adam D. Douglass
Publisher : Springer
ISBN 13 : 3319129139
Total Pages : 301 pages
Book Rating : 4.36/5 ( download)

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Download or read book New Techniques in Systems Neuroscience written by Adam D. Douglass and published by Springer. This book was released on 2015-04-13 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is essential reading for anyone wishing to understand the recent explosion of experimental tools in neuroscience that now make it possible to manipulate, record, and understand neuronal activity within the intact brain, and which are helping us learn how the many neurons that comprise a network act together to control behavior. Leaders in the field discuss the latest developments in optogenetics, functional imaging, circuit mapping, and the application of these tools to complex biological problems.

Author : Paul Miller
Publisher : MIT Press
ISBN 13 : 0262038250
Total Pages : 405 pages
Book Rating : 4.56/5 ( download)

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Download or read book An Introductory Course in Computational Neuroscience written by Paul Miller and published by MIT Press. This book was released on 2018-10-02 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Michael A. Arbib
Publisher : MIT Press
ISBN 13 : 0262335271
Total Pages : 808 pages
Book Rating : 4.70/5 ( download)

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Download or read book From Neuron to Cognition via Computational Neuroscience written by Michael A. Arbib and published by MIT Press. This book was released on 2016-11-04 with total page 808 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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