Principles Of Neural Information Processing
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Author | : Werner v. Seelen |
Publisher | : Springer |
Total Pages | : 110 |
Release | : 2015-06-30 |
Genre | : Technology & Engineering |
ISBN | : 3319201131 |
In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books ́ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework but also systems and signal theory. The most important message of the book and authors is: brains are evolved as a whole and a description of parts although necessary lets one miss the wood for the trees.
Author | : Peter Sterling |
Publisher | : MIT Press |
Total Pages | : 567 |
Release | : 2015-05-22 |
Genre | : Education |
ISBN | : 0262028700 |
Neuroscience research has exploded, with more than fifty thousand neuroscientists applying increasingly advanced methods. A mountain of new facts and mechanisms has emerged. And yet a principled framework to organize this knowledge has been missing. In this book, Peter Sterling and Simon Laughlin, two leading neuroscientists, strive to fill this gap, outlining a set of organizing principles to explain the whys of neural design that allow the brain to compute so efficiently. Setting out to "reverse engineer" the brain -- disassembling it to understand it -- Sterling and Laughlin first consider why an animal should need a brain, tracing computational abilities from bacterium to protozoan to worm. They examine bigger brains and the advantages of "anticipatory regulation"; identify constraints on neural design and the need to "nanofy"; and demonstrate the routes to efficiency in an integrated molecular system, phototransduction. They show that the principles of neural design at finer scales and lower levels apply at larger scales and higher levels; describe neural wiring efficiency; and discuss learning as a principle of biological design that includes "save only what is needed." Sterling and Laughlin avoid speculation about how the brain might work and endeavor to make sense of what is already known. Their distinctive contribution is to gather a coherent set of basic rules and exemplify them across spatial and functional scales.
Author | : Rodrigo Quian Quiroga |
Publisher | : CRC Press |
Total Pages | : 643 |
Release | : 2013-05-06 |
Genre | : Medical |
ISBN | : 1439853304 |
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 | : James V Stone |
Publisher | : |
Total Pages | : 214 |
Release | : 2018-05-15 |
Genre | : Computers |
ISBN | : 9780993367922 |
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.
Author | : Michael I. Jordan |
Publisher | : MIT Press |
Total Pages | : 1114 |
Release | : 1998 |
Genre | : Computers |
ISBN | : 9780262100762 |
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.
Author | : Rajesh P.N. Rao |
Publisher | : MIT Press |
Total Pages | : 348 |
Release | : 2002-03-29 |
Genre | : Medical |
ISBN | : 9780262264327 |
A survey of probabilistic approaches to modeling and understanding brain function. Neurophysiological, neuroanatomical, and brain imaging studies have helped to shed light on how the brain transforms raw sensory information into a form that is useful for goal-directed behavior. A fundamental question that is seldom addressed by these studies, however, is why the brain uses the types of representations it does and what evolutionary advantage, if any, these representations confer. It is difficult to address such questions directly via animal experiments. A promising alternative is to use probabilistic principles such as maximum likelihood and Bayesian inference to derive models of brain function. This book surveys some of the current probabilistic approaches to modeling and understanding brain function. Although most of the examples focus on vision, many of the models and techniques are applicable to other modalities as well. The book presents top-down computational models as well as bottom-up neurally motivated models of brain function. The topics covered include Bayesian and information-theoretic models of perception, probabilistic theories of neural coding and spike timing, computational models of lateral and cortico-cortical feedback connections, and the development of receptive field properties from natural signals.
Author | : John A. Hertz |
Publisher | : CRC Press |
Total Pages | : 352 |
Release | : 2018-03-08 |
Genre | : Science |
ISBN | : 0429968213 |
Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.
Author | : Xingui He |
Publisher | : Springer Science & Business Media |
Total Pages | : 240 |
Release | : 2010-07-05 |
Genre | : Computers |
ISBN | : 3540737626 |
For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.
Author | : David Sterratt |
Publisher | : Cambridge University Press |
Total Pages | : 553 |
Release | : 2023-10-05 |
Genre | : Science |
ISBN | : 1108483143 |
Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.
Author | : Henry Kennedy |
Publisher | : Springer |
Total Pages | : 173 |
Release | : 2016-03-10 |
Genre | : Medical |
ISBN | : 3319277774 |
This book has brought together leading investigators who work in the new arena of brain connectomics. This includes ‘macro-connectome’ efforts to comprehensively chart long-distance pathways and functional networks; ‘micro-connectome’ efforts to identify every neuron, axon, dendrite, synapse, and glial process within restricted brain regions; and ‘meso-connectome’ efforts to systematically map both local and long-distance connections using anatomical tracers. This book highlights cutting-edge methods that can accelerate progress in elucidating static ‘hard-wired’ circuits of the brain as well as dynamic interactions that are vital for brain function. The power of connectomic approaches in characterizing abnormal circuits in the many brain disorders that afflict humankind is considered. Experts in computational neuroscience and network theory provide perspectives needed for synthesizing across different scales in space and time. Altogether, this book provides an integrated view of the challenges and opportunities in deciphering brain circuits in health and disease.