Nonlinear Vision Determination Of Neural Receptive Fields Function And Networks
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Nonlinear Vision: Determination of Neural Receptive Fields, Function, and Networks by Robert B. Pinter Pdf
This text brings to vision research a treatment different from that often found in books on the subject in its emphasis on nonlinear aspects of vision, from human perception to eye cells of the fly. There is considerable emphasis on mathematics, which forms not only models but the algorithms for processing data.
Nonlinear Image Processing by Sanjit Mitra,Giovanni Sicuranza Pdf
This state-of-the-art book deals with the most important aspects of non-linear imaging challenges. The need for engineering and mathematical methods is essential for defining non-linear effects involved in such areas as computer vision, optical imaging, computer pattern recognition, and industrial automation challenges.
Author : Professor Vasilis Z. Marmarelis Publisher : John Wiley & Sons Page : 564 pages File Size : 45,8 Mb Release : 2004-09-03 Category : Medical ISBN : 0471469602
Nonlinear Dynamic Modeling of Physiological Systems by Professor Vasilis Z. Marmarelis Pdf
The study of nonlinearities in physiology has been hindered by the lack of effective ways to obtain nonlinear dynamic models from stimulus-response data in a practical context. A considerable body of knowledge has accumulated over the last thirty years in this area of research. This book summarizes that progress, and details the most recent methodologies that offer practical solutions to this daunting problem. Implementation and application are discussed, and examples are provided using both synthetic and actual experimental data. This essential study of nonlinearities in physiology apprises researchers and students of the latest findings and techniques in the field.
One of the most remarkable things about seeing is how effortless this complex task appears to be. This book provides a comprehensive overview of research on the myriad complexities of this task. Coverage includes such classic topics as color, spatial, and binocular vision, areas that have seen a recent explosion of new information such as motion vision, image formation and sampling, and areas where new tools have allowed a better investigation into processes (e.g. neural representation of shape, visual attention). Seeing is a needed reference for researchers specializing in visual perception and is suitable for advance courses on vision.
Visual Population Codes by Nikolaus Kriegeskorte,Gabriel Kreiman Pdf
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.
Advanced Methods of Physiological System Modeling by V.Z. Marmarelis Pdf
This volume is the third in a series entitled" Advanced Methods of Physiological System Modeling" and the fifth in a series of research volumes published by Plenum under the sponsorship of the Biomedical Simulations Resource (BMSR) at the Uni versity of Southern California in the context of dissemination activities supported by the Biomedical Research Technology Program of the National Center for Research Resources at the National Institutes of Health under Grant No. P41 RR-OI861. These volumes are edited by BMSR principal scientists and report on recent research de velopments in the area of physiological systems modeling, as well as on advanced methods for analysis of physiological signals and data. As in the previous two volumes of this series, the work reported herein is con cerned with the development of advanced modeling methodologies and their novel application to problems of biomedical interest, with emphasis on nonlinear aspects of physiological function. The term "advanced methodologies" is used to indicate that the scope of this work extends beyond the ordinary type of analysis, which is confined traditionally to the linear domain. As the importance of nonlinearities in understanding the complex mechanisms of physiological function is increasingly recognized, the need for effective and practical modeling methodologies that address the issue of nonlinear dynamics in life sciences becomes more and more pressing.
Genomics and Proteomics Engineering in Medicine and Biology by Metin Akay Pdf
Current applications and recent advances in genomics and proteomics Genomics and Proteomics Engineering in Medicine and Biology presents a well-rounded, interdisciplinary discussion of a topic that is at the cutting edge of both molecular biology and bioengineering. Compiling contributions by established experts, this book highlights up-to-date applications of biomedical informatics, as well as advancements in genomics-proteomics areas. Structures and algorithms are used to analyze genomic data and develop computational solutions for pathological understanding. Topics discussed include: Qualitative knowledge models Interpreting micro-array data Gene regulation bioinformatics Methods to analyze micro-array Cancer behavior and radiation therapy Error-control codes and the genome Complex life science multi-database queries Computational protein analysis Tumor and tumor suppressor proteins interactions
Encyclopedia of Optical and Photonic Engineering (Print) - Five Volume Set by Craig Hoffman,Ronald Driggers Pdf
The first edition of the Encyclopedia of Optical and Photonic Engineering provided a valuable reference concerning devices or systems that generate, transmit, measure, or detect light, and to a lesser degree, the basic interaction of light and matter. This Second Edition not only reflects the changes in optical and photonic engineering that have occurred since the first edition was published, but also: Boasts a wealth of new material, expanding the encyclopedia’s length by 25 percent Contains extensive updates, with significant revisions made throughout the text Features contributions from engineers and scientists leading the fields of optics and photonics today With the addition of a second editor, the Encyclopedia of Optical and Photonic Engineering, Second Edition offers a balanced and up-to-date look at the fundamentals of a diverse portfolio of technologies and discoveries in areas ranging from x-ray optics to photon entanglement and beyond. This edition’s release corresponds nicely with the United Nations General Assembly’s declaration of 2015 as the International Year of Light, working in tandem to raise awareness about light’s important role in the modern world. Also Available Online This Taylor & Francis encyclopedia is also available through online subscription, offering a variety of extra benefits for researchers, students, and librarians, including: Citation tracking and alerts Active reference linking Saved searches and marked lists HTML and PDF format options Contact Taylor and Francis for more information or to inquire about subscription options and print/online combination packages. US: (Tel) 1.888.318.2367; (E-mail) [email protected] International: (Tel) +44 (0) 20 7017 6062; (E-mail) [email protected]
Author : Philip S. Ulinski Publisher : Springer Science & Business Media Page : 587 pages File Size : 44,9 Mb Release : 2012-12-06 Category : Medical ISBN : 9781461549031
This volume is devoted to mathematical models of the cortex. Computational models of individual neurons and ensembles of neurons are increasingly used in research on cortical organization and function. This is, in part, because of the now ubiquitous presence of powerful and affordable computers. The volume begins with a short history of models of cortical neurons and circuitry that introduces the principal modeling styles. An attempt has been made throughout the volume to make it accessible to readers with minimal mathematical backgrounds.
Advanced Mathematical Approach to Biology by Takeyuki Hida Pdf
This volume consists of three papers, the first paper by T Ray aims to create an instantiation of evolution by natural selection in the computational medium. This creates a conceptual problem that requires considerable art to solve.The second paper by K-I Naka and V Bhanot discusses an interesting application of white noise analysis to the retinal physiology. It deals with identification of the retina mathematically, and one can see profound results that can be discovered only by using white noise analysis.The last paper by T Hida illustrates the use of white noise analysis for biologists. Readers will see the types of topics to which white noise analysis can be applied and how to apply the theory to actual phenomena.
From Statistics to Neural Networks by Vladimir Cherkassky,Jerome H. Friedman,Harry Wechsler Pdf
The NATO Advanced Study Institute From Statistics to Neural Networks, Theory and Pattern Recognition Applications took place in Les Arcs, Bourg Saint Maurice, France, from June 21 through July 2, 1993. The meeting brought to gether over 100 participants (including 19 invited lecturers) from 20 countries. The invited lecturers whose contributions appear in this volume are: L. Almeida (INESC, Portugal), G. Carpenter (Boston, USA), V. Cherkassky (Minnesota, USA), F. Fogelman Soulie (LRI, France), W. Freeman (Berkeley, USA), J. Friedman (Stanford, USA), F. Girosi (MIT, USA and IRST, Italy), S. Grossberg (Boston, USA), T. Hastie (AT&T, USA), J. Kittler (Surrey, UK), R. Lippmann (MIT Lincoln Lab, USA), J. Moody (OGI, USA), G. Palm (U1m, Germany), B. Ripley (Oxford, UK), R. Tibshirani (Toronto, Canada), H. Wechsler (GMU, USA), C. Wellekens (Eurecom, France) and H. White (San Diego, USA). The ASI consisted of lectures overviewing major aspects of statistical and neural network learning, their links to biological learning and non-linear dynamics (chaos), and real-life examples of pattern recognition applications. As a result of lively interactions between the participants, the following topics emerged as major themes of the meeting: (1) Unified framework for the study of Predictive Learning in Statistics and Artificial Neural Networks (ANNs); (2) Differences and similarities between statistical and ANN methods for non parametric estimation from examples (learning); (3) Fundamental connections between artificial learning systems and biological learning systems.
What can simple brains teach us about how vision works by Davide Zoccolan,David D. Cox,Andrea Benucci, R. Clay Reid Pdf
Vision is the process of extracting behaviorally-relevant information from patterns of light that fall on retina as the eyes sample the outside world. Traditionally, nonhuman primates (macaque monkeys, in particular) have been viewed by many as the animal model-of-choice for investigating the neuronal substrates of visual processing, not only because their visual systems closely mirror our own, but also because it is often assumed that “simpler” brains lack advanced visual processing machinery. However, this narrow view of visual neuroscience ignores the fact that vision is widely distributed throughout the animal kingdom, enabling a wide repertoire of complex behaviors in species from insects to birds, fish, and mammals. Recent years have seen a resurgence of interest in alternative animal models for vision research, especially rodents. This resurgence is partly due to the availability of increasingly powerful experimental approaches (e.g., optogenetics and two-photon imaging) that are challenging to apply to their full potential in primates. Meanwhile, even more phylogenetically distant species such as birds, fish, and insects have long been workhorse animal models for gaining insight into the core computations underlying visual processing. In many cases, these animal models are valuable precisely because their visual systems are simpler than the primate visual system. Simpler systems are often easier to understand, and studying a diversity of neuronal systems that achieve similar functions can focus attention on those computational principles that are universal and essential. This Research Topic provides a survey of the state of the art in the use of animal models of visual functions that are alternative to macaques. It includes original research, methods articles, reviews, and opinions that exploit a variety of animal models (including rodents, birds, fishes and insects, as well as small New World monkey, the marmoset) to investigate visual function. The experimental approaches covered by these studies range from psychophysics and electrophysiology to histology and genetics, testifying to the richness and depth of visual neuroscience in non-macaque species.
Perceiving in Depth, Volume 1 by Ian P. Howard,Brian J. Rogers Pdf
The three-volume work Perceiving in Depth is a sequel to Binocular Vision and Stereopsis and to Seeing in Depth, both by Ian P. Howard and Brian J. Rogers. This work is much broader in scope than the previous books and includes mechanisms of depth perception by all senses, including aural, electrosensory organs, and the somatosensory system. Volume 1 reviews sensory coding, psychophysical and analytic procedures, and basic visual mechanisms. Volume 2 reviews stereoscopic vision. Volume 3 reviews all mechanisms of depth perception other than stereoscopic vision. The three volumes are extensively illustrated and referenced and provide the most detailed review of all aspects of perceiving the three-dimensional world.Volume 1 starts with a review of the history of visual science from the ancient Greeks to the early 20th century with special attention devoted to the discovery of the principles of perspective and stereoscopic vision. The first chapter also contains an account of early visual display systems, such as panoramas and peepshows, and the development of stereoscopes and stereophotography. A chapter on the psychophysical and analytic procedures used in investigations of depth perception is followed by a chapter on sensory coding and the geometry of visual space. An account of the structure and physiology of the primate visual system proceeds from the eye through the LGN to the visual cortex and higher visual centers. This is followed by a review of the evolution of visual systems and of the development of the mammalian visual system in the embryonic and post-natal periods, with an emphasis on experience-dependent neural plasticity. An account of the development of perceptual functions, especially depth perception, is followed by a review of the effects of early visual deprivation during the critical period of neural plasticity on amblyopia and other defects in depth perception. Volume 1 ends with accounts of the accommodation mechanism of the human eye and vergence eye movements.
Fuzzy Logic and Soft Computing by Bernadette Bouchon-Meunier,Ronald R. Yager,Lotfi Asker Zadeh Pdf
Soft computing is a new, emerging discipline rooted in a group of technologies that aim to exploit the tolerance for imprecision and uncertainty in achieving solutions to complex problems. The principal components of soft computing are fuzzy logic, neurocomputing, genetic algorithms and probabilistic reasoning.This volume is a collection of up-to-date articles giving a snapshot of the current state of the field. It covers the whole expanse, from theoretical foundations to applications. The contributors are among the world leaders in the field.
