The New Visual Neurosciences

Author: John Simon Werner
Publisher: MIT Press (MA)
ISBN: 9780262019163
Format: PDF, Docs
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Visual science is the model system for neuroscience, its findings relevant to all other areas. This essential reference to contemporary visual neuroscience covers the extraordinary range of the field today, from molecules and cell assemblies to systems and therapies. It provides a state-of-the art companion to the earlier book The Visual Neurosciences (MIT Press, 2003). This volume covers the dramatic advances made in the last decade, offering new topics, new authors, and new chapters. The New Visual Neurosciences assembles groundbreaking research, written by international authorities. Many of the 112 chapters treat seminal topics not included in the earlier book. These new topics include retinal feature detection; cortical connectomics; new approaches to mid-level vision and spatiotemporal perception; the latest understanding of how multimodal integration contributes to visual perception; new theoretical work on the role of neural oscillations in information processing; and new molecular and genetic techniques for understanding visual system development. An entirely new section covers invertebrate vision, reflecting the importance of this research in understanding fundamental principles of visual processing. Another new section treats translational visual neuroscience, covering recent progress in novel treatment modalities for optic nerve disorders, macular degeneration, and retinal cell replacement. The New Visual Neurosciences is an indispensable reference for students, teachers, researchers, clinicians, and anyone interested in contemporary neuroscience. Associate EditorsMarie Burns, Joy Geng, Mark Goldman, James Handa, Andrew Ishida, George R. Mangun, Kimberley McAllister, Bruno Olshausen, Gregg Recanzone, Mandyam Srinivasan, W.Martin Usrey, Michael Webster, David Whitney SectionsRetinal Mechanisms and ProcessesOrganization of Visual PathwaysSubcortical ProcessingProcessing in Primary Visual CortexBrightness and ColorPattern, Surface, and ShapeObjects and ScenesTime, Motion, and DepthEye MovementsCortical Mechanisms of Attention, Cognition, and Multimodal IntegrationInvertebrate VisionTheoretical PerspectivesMolecular and Developmental ProcessesTranslational Visual Neuroscience

Computational Models of Visual Processing

Author: Michael S. Landy
Publisher: MIT Press
ISBN: 9780262121552
Format: PDF, Kindle
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The more than twenty contributions in this book, all new and previously unpublished, provide an up-to-date survey of contemporary research on computational modeling of the visual system. The approaches represented range from neurophysiology to psychophysics, and from retinal function to the analysis of visual cues to motion, color, texture, and depth. The contributions are linked thematically by a consistent consideration of the links between empirical data and computational models in the study of visual function.An introductory chapter by Edward Adelson and James Bergen gives a new and elegant formalization of the elements of early vision. Subsequent sections treat receptors and sampling, models of neural function, detection and discrimination, color and shading, motion and texture, and 3D shape. Each section is introduced by a brief topical review and summary.Michael S. Landy is Associate Professor of Psychology at New York University where J. Anthony Movshon is Professor of Neural Science and Psychology and Director of the Center for Neural Science.Contributors: Edward H. Adelson. Albert J. Ahumada, Jr., James R. Bergen. David G. Birch. David H. Brainard. Heinrich H. Bülthoff. Charles Chubb. Nancy J. Coletta. Michael D'Zmura. John P. Frisby. Norma Graham. Norberto M. Grzywacz. P. William Haake. Michael J. Hawken. David J. Heeger. Donald C. Hood. Elizabeth B. Johnston. Daniel Kersten. Michael S. Landy. Peter Lennie. J. Stephen Mansfield. J. Anthony Movshon. Jacob Nachmias. Andrew J. Parker. Denis G. Pelli. Stephen B. Pollard. R. Clay Reid. Robert Shapley. Carlo L. M. Tiana. Brian A. Wandell. Andrew B. Watson. David R. Williams. Hugh R. Wilson. Yuede. Yang. Alan L. Yuille.

Scene Vision

Author: Kestutis Kveraga
Publisher: MIT Press
ISBN: 0262027852
Format: PDF, ePub, Mobi
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In this volume, pioneering researchers address the visual cognition of scenes from neuroimaging, psychology, modeling, electrophysiology and computer vision perspectives.

Vision Science

Author: Stephen E. Palmer
Publisher: MIT Press
ISBN: 0262304015
Format: PDF, Docs
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This book revolutionizes how vision can be taught to undergraduate and graduate students in cognitive science, psychology, and optometry. It is the first comprehensive textbook on vision to reflect the integrated computational approach of modern research scientists. This new interdisciplinary approach, called "vision science," integrates psychological, computational, and neuroscientific perspectives. The book covers all major topics related to vision, from early neural processing of image structure in the retina to high-level visual attention, memory, imagery, and awareness. The presentation throughout is theoretically sophisticated yet requires minimal knowledge of mathematics. There is also an extensive glossary, as well as appendices on psychophysical methods, connectionist modeling, and color technology. The book will serve not only as a comprehensive textbook on vision, but also as a valuable reference for researchers in cognitive science, psychology, neuroscience, computer science, optometry, and philosophy.

Visual Cortex and Deep Networks

Author: Tomaso A. Poggio
Publisher: MIT Press
ISBN: 0262336723
Format: PDF, Mobi
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The ventral visual stream is believed to underlie object recognition in primates. Over the past fifty years, researchers have developed a series of quantitative models that are increasingly faithful to the biological architecture. Recently, deep learning convolution networks -- which do not reflect several important features of the ventral stream architecture and physiology -- have been trained with extremely large datasets, resulting in model neurons that mimic object recognition but do not explain the nature of the computations carried out in the ventral stream. This book develops a mathematical framework that describes learning of invariant representations of the ventral stream and is particularly relevant to deep convolutional learning networks. The authors propose a theory based on the hypothesis that the main computational goal of the ventral stream is to compute neural representations of images that are invariant to transformations commonly encountered in the visual environment and are learned from unsupervised experience. They describe a general theoretical framework of a computational theory of invariance (with details and proofs offered in appendixes) and then review the application of the theory to the feedforward path of the ventral stream in the primate visual cortex.

Visual Population Codes

Author: Nikolaus Kriegeskorte
Publisher: MIT Press
ISBN: 0262016249
Format: PDF, ePub
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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.