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Computational Maps in the Visual Cortex
by Risto Miikkulainen

Computational Maps in the Visual Cortex presents a unified computational approach to understanding the structure, development, and function of the visual cortex.

Computational Maps in the Visual Cortex reviews the current theories of the visual cortex and the biological data on which they are based, and presents a detailed analysis of the laterally connected self-organizing map model and results obtained to date.



1. Introduction

  • Input-Driven Self-Organization
  • Constructing Visual Function
  • Perceptual Grouping
  • Approach
  • Guide for the Reader

2. Biological Background

  • Visual System Organization
  • Lateral Connections
  • Genetic Versus Environmental Factors in Development
  • Temporal Coding

3. Computational Foundations

  • Computational Units
  • Temporal Coding
  • Adaptation
  • Self-Organizing Maps
  • Knowledge Representation in Maps

Input-Driven Self-Organization

4. Lissom: A Computational Map Model of V1

  • Motivation: Cortical Maps
  • The Lissom Architecture
  • Response Generation
  • Learning
  • Self-Organizing Process

5. Development of Maps and Connections

  • Biological Background
  • Computational Models
  • Orientation Maps
  • Ocular Dominance Maps
  • Direction Selectivity Maps
  • Combined Maps of Multiple Features
  • Discussion

6. Understanding Plasticity

  • Biological and Computational Background
  • The Reduced Lissom Model
  • Retinal Lesions
  • Cortical Lesions

7. Understanding Visual Performance: The Tilt Aftereffect

  • Psychophysical and Computational Background
  • Method
  • Results
  • Anaysis

Constructing Visual Function

8. Hlissom: A Hierarchical Model

  • Motivation: Synergy of Nature and Nurture
  • The Hierarchical Architecture
  • Inputs, Activation and Learning
  • Effect of Input Sequence and Initial Organization

9. Understanding Low-Level Development: Orientation Maps

  • Biological Motivation
  • Prenatal Development
  • Postnatal Development
  • Prenatal and Postnatal Contributions

10. Understanding High-Level Development: Face Detection

  • Psychophysical and Computational Background
  • Prenatal Development
  • Postnatal Development

Perceptual Grouping

11. Pglissom: A Perceptual Grouping Model

  • Motivation: Temporal Coding
  • The Self-Organization and Grouping Architecture
  • Spiking Unit Model
  • Learning
  • Self-Organizing Process

12. Temporal Coding

  • Binding Through Synchronization
  • Segmentation Through Desynchronization
  • Robustness Against Variation and Noise

13. Understanding Perceptual Grouping: Contour Integration

  • Psychophysical and Computational Background
  • Contour Integration and Segmentation
  • Contour Completion and Illusory Contours
  • Influence of Input Distribution on Anatomy and Performance

Evaluation and Future Directions

14. Computations in Visual Maps

  • Visual Coding in the Cortex
  • Visual Coding in Lissom
  • Visual Coding for High-Level Tasks

15. Scaling Lissom Simulations

  • Parameter Scaling Approach
  • Scaling Equations
  • Forming Large Maps: The Glissom Approach
  • Glissom Scaling
  • Scaling to Cortical Dimensions

16. Discussion: Biological Assumptions and Predictions

  • Self-Organization
  • Genetically Driven Development
  • Temporal Coding

17. Future Work: Computational Directions

  • Extensions to the Lissom Mechanisms
  • Modeling New Phenomena with Lissom
  • New Research Directions
  • The Topograohica Cortical Map Simular


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Computational Maps in the Visual Cortex
by Risto Miikkulainen
2005 • 538 pages • $178.00 + shipping
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