Download or read book Information Theory and the Brain written by Roland Baddeley and published by Cambridge University Press. This book was released on 2000-05-15 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with information theory, a new and expanding area of neuroscience which provides a framework for understanding neuronal processing.
Download or read book Principles of Neural Information Theory written by James V Stone and published by . This book was released on 2018-05-15 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this richly illustrated book, it is shown how Shannon's mathematical theory of information defines absolute limits on neural efficiency; limits which ultimately determine the neuroanatomical microstructure of the eye and brain. Written in an informal style this is an ideal introduction to cutting-edge research in neural information theory.
Download or read book Information Theory in Neuroscience written by Stefano Panzeri and published by MDPI. This book was released on 2019-03-15 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the ultimate information processing device, the brain naturally lends itself to being studied with information theory. The application of information theory to neuroscience has spurred the development of principled theories of brain function, and has led to advances in the study of consciousness, as well as to the development of analytical techniques to crack the neural code—that is, to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling the precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative testing of hypotheses about how the brain encodes and transmits the information used for specific functions across areas. This Special Issue presents twelve original contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience.
Download or read book Information Theory in Neuroscience written by and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the ultimate information processing device, the brain naturally lends itself to being studied with information theory. The application of information theory to neuroscience has spurred the development of principled theories of brain function, and has led to advances in the study of consciousness, as well as to the development of analytical techniques to crack the neural code--that is, to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling the precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative testing of hypotheses about how the brain encodes and transmits the information used for specific functions across areas. This Special Issue presents twelve original contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience.
Download or read book An Introduction to Transfer Entropy written by Terry Bossomaier and published by Springer. This book was released on 2016-11-15 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers a relatively new metric in complex systems, transfer entropy, derived from a series of measurements, usually a time series. After a qualitative introduction and a chapter that explains the key ideas from statistics required to understand the text, the authors then present information theory and transfer entropy in depth. A key feature of the approach is the authors' work to show the relationship between information flow and complexity. The later chapters demonstrate information transfer in canonical systems, and applications, for example in neuroscience and in finance. The book will be of value to advanced undergraduate and graduate students and researchers in the areas of computer science, neuroscience, physics, and engineering.
Download or read book Analyzing Neural Time Series Data written by Mike X Cohen and published by MIT Press. This book was released on 2014-01-17 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings. This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals. It explains the conceptual, mathematical, and implementational (via Matlab programming) aspects of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and local field potential (LFP) recordings from humans and nonhuman animals. It is the only book on the topic that covers both the theoretical background and the implementation in language that can be understood by readers without extensive formal training in mathematics, including cognitive scientists, neuroscientists, and psychologists. Readers who go through the book chapter by chapter and implement the examples in Matlab will develop an understanding of why and how analyses are performed, how to interpret results, what the methodological issues are, and how to perform single-subject-level and group-level analyses. Researchers who are familiar with using automated programs to perform advanced analyses will learn what happens when they click the “analyze now” button. The book provides sample data and downloadable Matlab code. Each of the 38 chapters covers one analysis topic, and these topics progress from simple to advanced. Most chapters conclude with exercises that further develop the material covered in the chapter. Many of the methods presented (including convolution, the Fourier transform, and Euler's formula) are fundamental and form the groundwork for other advanced data analysis methods. Readers who master the methods in the book will be well prepared to learn other approaches.
Download or read book Information Theory Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.
Download or read book Spikes written by Fred Rieke and published by MIT Press (MA). This book was released on 1997 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intended for neurobiologists with an interest in mathematical analysis of neural data as well as the growing number of physicists and mathematicians interested in information processing by "real" nervous systems, Spikes provides a self-contained review of relevant concepts in information theory and statistical decision theory.
Download or read book Directed Information Measures in Neuroscience written by Michael Wibral and published by Springer. This book was released on 2014-03-20 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis of information transfer has found rapid adoption in neuroscience, where a highly dynamic transfer of information continuously runs on top of the brain's slowly-changing anatomical connectivity. Measuring such transfer is crucial to understanding how flexible information routing and processing give rise to higher cognitive function. Directed Information Measures in Neuroscience reviews recent developments of concepts and tools for measuring information transfer, their application to neurophysiological recordings and analysis of interactions. Written by the most active researchers in the field the book discusses the state of the art, future prospects and challenges on the way to an efficient assessment of neuronal information transfer. Highlights include the theoretical quantification and practical estimation of information transfer, description of transfer locally in space and time, multivariate directed measures, information decomposition among a set of stimulus/responses variables and the relation between interventional and observational causality. Applications to neural data sets and pointers to open source software highlight the usefulness of these measures in experimental neuroscience. With state-of-the-art mathematical developments, computational techniques and applications to real data sets, this book will be of benefit to all graduate students and researchers interested in detecting and understanding the information transfer between components of complex systems.
Download or read book Novelty Information and Surprise written by Günther Palm and published by Springer Nature. This book was released on 2023-01-02 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This revised edition offers an approach to information theory that is more general than the classical approach of Shannon. Classically, information is defined for an alphabet of symbols or for a set of mutually exclusive propositions (a partition of the probability space Ω) with corresponding probabilities adding up to 1. The new definition is given for an arbitrary cover of Ω, i.e. for a set of possibly overlapping propositions. The generalized information concept is called novelty and it is accompanied by two concepts derived from it, designated as information and surprise, which describe "opposite" versions of novelty, information being related more to classical information theory and surprise being related more to the classical concept of statistical significance. In the discussion of these three concepts and their interrelations several properties or classes of covers are defined, which turn out to be lattices. The book also presents applications of these concepts, mostly in statistics and in neuroscience.
Download or read book Brain Arousal and Information Theory written by Donald W PFAFF and published by Harvard University Press. This book was released on 2009-06-30 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Arousal is fundamental to all cognition. It is intuitively obvious, absolutely necessary, but what exactly is it? In Brain Arousal and Information Theory, Donald Pfaff presents a daring perspective on this long-standing puzzle. Pfaff argues that, beneath our mental functions and emotional dispositions, a primitive neuronal system governs arousal. Employing the simple but powerful framework of information theory, Pfaff revolutionizes our understanding of arousal systems in the brain. Starting with a review of the neuroanatomical, neurophysiological, and neurochemical components of arousal, Pfaff asks us to look at the gene networks and neural pathways underlying the brain's arousal systems much as a design engineer would contemplate information systems. This allows Pfaff to postulate that there is a bilaterally symmetric, bipolar system universal among mammals that readies the animal or the human being to respond to stimuli, initiate voluntary locomotion, and react to emotional challenges. Applying his hypothesis to heightened states of arousal--sex and fear--Pfaff shows us how his theory opens new scientific approaches to understanding the structure of brain arousal. A major synthesis of disparate data by a preeminent neuroscientist, Brain Arousal and Information Theory challenges current thinking about cognition and behavior. Whether you subscribe to Pfaff's theory or not, this book will stimulate debate about the nature of arousal itself.
Download or read book Information Theory Tools for Visualization written by Min Chen and published by A K PETERS. This book was released on 2022-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information Theory tools, which are widely used in fields such as communication, physics, genetics, neuroscience and many others, have emerged as useful transversal tools in the field of visualization. Information Theory Tools for Visualization covers both the basic theoretical concepts behind these tools as well as their use in different visualization applications. Drawing together the work of a number of leading experts in this field, this book offers a useful guide to which problems can be solved with Information Theory tools as well as the means of doing so. Following an introduction to Information Theory, the book enlists five chapters to explore five major aspects of visualization, including theoretical foundation, viewpoint optimization, volume visualization, flow visualization, and information visualization. With the aid of many examples, each chapter provides a comprehensive description of how Information Theory tools can be used to solve visualization problems. Key features, First book solely dedicated to information Theory techniques for visualization, Written by leading experts in the field, Provides comprehensive coverage of the scientific literature on Information Theory tools for visualization, Offers a range of applications of Information Theory in visualization, including volume rendering, streamline seeding, viewpoint selection, summary tree construction, glyph-based visualization, multivariate data exploration, process optimization for visual analytics workflows, and so forth, Intended for graduate students and researchers in the fields of visualization, graphics, and image processing, this book assumes a basic understanding of visualization but also offers a handy sketch to basic concepts. Book jacket.
Download or read book Consciousness written by Rodrick Wallace and published by Springer Science & Business Media. This book was released on 2005-04-14 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book makes formal, detailed, application of what Adams has described as 'the informational turn in philosophy' to the global neuronal workspace (GNW) model of consciousness. It uses an extended statistical model of cognitive process, based on the Shannon-McMillan Theorem and its corollaries, to incorporate the effects of embedding physiological, social, and cultural contextual constraints which operate more slowly than the workspace itself, but severely limit the possible realms available to that workspace, and hence to consciousness itself. The resulting 'biopsychosociocultural' treatment directly addresses criticisms of brain-only models of consciousness which have been raised in cultural psychology and philosophy, while remaining true to the current neuroscience perspective. This is the first formal, comprehensive, and reasonably rigorous, mathematical treatment of the GNW and is the only one to include the effects of embedding contexts in a 'natural' manner.
Download or read book Information Theory Inference And Learning Algorithms written by MACKAY and published by . This book was released on with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.
Download or read book Information Processing in the Cortex written by Ad Aertsen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a tradition of theoretical brain science which started in the forties (Wiener, McCulloch, Turing, Craik, Hebb). This was continued by a small number of people without interruption up to the present. It has definitely provided main guiding lines for brain science, the devel opment of which has been spectacular in the last decades. However, within the bulk of experimental neuroscience, the theoreticians some times had a difficult stand, since it was felt that the times were not ripe yet and the methods not yet available for a development of a true theoretical speciality in this field. Thus theory remained in the hands of a fairly small club which recruited its members from theoretical physicists, mathematicians and some experimentalists with amateurish theoretical leanings. The boom of approaches which go by the name of 'computational neuroscience', 'neuronal networks', 'associative mem ory', 'spinglass theory', 'parallel processing' etc. should not blind one for the fact that the group of people professionally interested in real istic models of brain function up to the present date remains rather small and suffers from a lack of professional organization. It was against this background that we decided to organize a meet ing on Theoretical Brain Science. The meeting was held April 18 - 20, 1990 and took place at Schloss Ringberg, West-Germany, a facility sponsored by the Max-Planck-Society.
Download or read book Meaningful Information written by Anthony Reading and published by Springer Science & Business Media. This book was released on 2011-06-16 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces a radically new way of thinking about information and the important role it plays in living systems. It opens up new avenues for exploring how cells and organisms change and adapt, since the ability to detect and respond to meaningful information is the key that enables them to receive their genetic heritage, regulate their internal milieu, and respond to changes in their environment. It also provides a way of resolving Descartes’ dilemma by explaining the workings of the brain in non-mechanical terms that are not tainted by spiritual or metaphysical beliefs. The types of meaningful information that different species and different cell types are able to detect are finely matched to the ecosystem in which they live, for natural selection has shaped what they need to know to function effectively in those circumstances. Biological detection and response systems range from the chemical configurations that govern genes and cell life to the relatively simple tropisms that guide single-cell organisms, the rudimentary nervous systems of invertebrates, and the complex neuronal structures of mammals and primates. The scope of meaningful information that can be detected and responded to reaches its peak in our own species, as exemplified by our special abilities in language, cognition, emotion, and consciousness, all of which are explored within this new framework.
Download or read book The Evolution of Biological Information written by Christoph Adami and published by Princeton University Press. This book was released on 2024-01-16 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why information is the unifying principle that allows us to understand the evolution of complexity in nature More than 150 years after Darwin’s revolutionary On the Origin of Species, we are still attempting to understand and explain the amazing complexity of life. Although we now know how evolution proceeds to build complexity from simple ingredients, quantifying this complexity is still a difficult undertaking. In this book, Christoph Adami offers a new perspective on Darwinian evolution by viewing it through the lens of information theory. This novel theoretical stance sheds light on such matters as how viruses evolve drug resistance, how cells evolve to communicate, and how intelligence evolves. By this account, information emerges as the central unifying principle behind all of biology, allowing us to think about the origin of life—on Earth and elsewhere—in a systematic manner. Adami, a leader in the field of computational biology, first provides an accessible introduction to the information theory of biomolecules and then shows how to apply these tools to measure information stored in genetic sequences and proteins. After outlining the experimental evidence of the evolution of information in both bacteria and digital organisms, he describes the evolution of robustness in viruses; the cooperation among cells, animals, and people; and the evolution of brains and intelligence. Building on extensive prior work in bacterial and digital evolution, Adami establishes that (expanding on Dobzhansky’s famous remark) nothing in biology makes sense except in the light of information. Understanding that information is the foundation of all life, he argues, allows us to see beyond the particulars of our way of life to glimpse what life might be like in other worlds.
