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Models of Neural Networks IV

Early Vision and Attention

  • Book
  • © 2002

Overview

Editors:
  1. J. Leo Hemmen

    1. Institut für Theoretische Physik, Technische Universität München, Garching bei München, Germany

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  2. Jack D. Cowan

    1. Department of Mathematics, University of Chicago, Chicago, USA

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  3. Eytan Domany

    1. Department of Electronics, Weizmann Institute of Science, Rehovot, Israel

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Part of the book series: Physics of Neural Networks (NEURAL NETWORKS)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xiii
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  2. Neurons, Networks, and Cognition: An Introduction to Neural Modeling

    • J. A. Hertz
    Pages 1-46

  3. The Gaze Control System

    • John van Opstal
    Pages 47-95

  4. Integrating Anatomy and Physiology of the Primary Visual Pathway: From LGN to Cortex

    • K. Funke, Z. F. Kisvárday, M. Volgushev, F. Wörgötter
    Pages 97-182

  5. Neural Principles of Preattentive Scene Segmentation: Hints from Cortical Recordings, Related Models, and Perception

    • Reinhard Eckhorn
    Pages 183-216

  6. Figure-Ground Segregation and Brightness Perception at Illusory Contours: A Neuronal Model

    • E. Peterhans, R. van der Zwan, B. Heider, F. Heitger
    Pages 217-245

  7. Controlling the Focus of Visual Selective Attention

    • Ernst Niebur, Laurent Itti, Christof Koch
    Pages 247-276

  8. Activity—Gating Attentional Networks

    • J. Eggert, J. L. van Hemmen
    Pages 277-312

  9. Timing and Counting Precision in the Blowfly Visual System

    • Rob de Ruyter, William Bialek
    Pages 313-371

  10. Paradigms for Computing with Spiking Neurons

    • Wolfgang Maass
    Pages 373-402

  11. Back Matter

    Pages 403-413
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Keywords

About this book

Close this book for a moment and look around you. You scan the scene by directing your attention, and gaze, at certain specific objects. Despite the background, you discern them. The process is partially intentional and partially preattentive. How all this can be done is described in the fourth volume of Models of Neural Networks devoted to Early Vision and Atten­ tion that you are holding in your hands. Early vision comprises the first stages of visual information processing. It is as such a scientific challenge whose clarification calls for a penetrating review. Here you see the result. The Heraeus Foundation (Hanau) is to be thanked for its support during the initial phase of this project. John Hertz, who has extensive experience in both computational and ex­ perimental neuroscience, provides in "Neurons, Networks, and Cognition" to neural modeling. John Van Opstal explains in a theoretical introduction "The Gaze Control System" how the eye's gaze control is performed and presents a novel theoretical description incorporating recent experimental results. We then turn to the relay stations thereafter, the lateral genicu­ late nucleus (LGN) and the primary visual cortex. Their anatomy, phys­ iology, functional relations, and ensuing response properties are carefully analyzed by Klaus Funke et al. in "Integrating Anatomy and Physiology of the Primary Visual Pathway: From LGN to Cortex", one of the most comprehensive reviews that is available at the moment.

Editors and Affiliations

  • Institut für Theoretische Physik, Technische Universität München, Garching bei München, Germany

    J. Leo Hemmen

  • Department of Mathematics, University of Chicago, Chicago, USA

    Jack D. Cowan

  • Department of Electronics, Weizmann Institute of Science, Rehovot, Israel

    Eytan Domany

Bibliographic Information

  • Book Title: Models of Neural Networks IV

  • Book Subtitle: Early Vision and Attention

  • Editors: J. Leo Hemmen, Jack D. Cowan, Eytan Domany

  • Series Title: Physics of Neural Networks

  • DOI: https://doi.org/10.1007/978-0-387-21703-1

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 2002

  • Hardcover ISBN: 978-0-387-95105-8Published: 09 November 2001

  • Softcover ISBN: 978-1-4419-2875-7Published: 14 December 2011

  • eBook ISBN: 978-0-387-21703-1Published: 09 November 2012

  • Series ISSN: 0939-3145

  • Edition Number: 1

  • Number of Pages: XIII, 413

  • Number of Illustrations: 87 b/w illustrations

  • Topics: Artificial Intelligence, Complexity

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