Visual pattern analyzers [electronic resource] / Norma Van Surdam Graham.

Graham, Norma Van Surdam.
New York : Oxford University Press, 1989.
Oxford psychology series ; no. 16.
Oxford science publications.
Oxford psychology series ; no. 16
Oxford science publications
1 online resource (663 p.)
Pattern perception.
Form perception.
Electronic books.
Organized to help the reader find needed information quickly and easily, this book emphasizes psychophysical experiments which measure the detection and identification of near-threshold patterns and the mathematical models used to draw inferences from experimental results.
Contents; Part I. INTRODUCTION; 1. Neurophysiology and Psychophysics; 1.1 Two Themes-Pattern Vision and Analyzers; 1.2 Analyzers in Color Vision as an Example; 1.3 Two Cautions About Analyzers; 1.4 Terminology-Responses Versus Outputs; 1.5 Models of Near-Threshold Pattern Vision-An Overview; 1.6 Neurophysiology and Pattern Vision; 1.7 Spatial Characteristics of Visual Neurons; 1.8 Temporal Characteristics of Visual Neurons; 1.9 Other Characteristics of Visual Neurons; 1.10 Some Terminology: Analyzer, Neuron, Mechanism, Channel, and Element; 1.11 Five Psychophysical Paradigms
1.12 Some Practical Matters1.13 Summary; Notes; 2. Some Mathematics; 2.1 Sinusoids and Fourier Analysis; 2.2 Lines and Points and Impulses (Delta Functions); 2.3 Windowed Sine Waves-Gabor Functions; 2.4 The Fourier Transform of a Sinusoidal Patch; 2.5 Linear Systems and Points; 2.6 Linear Systems and Sines; 2.7 How Stimulus Decompositions are Useful; 2.8 Selectivity of Analyzers; 2.9 Summary; 2.10 Appendix. Fourier Transforms of Sinusoidal, Delta, Gaussian, and Gabor Functions; Part II. ADAPTATION; 3. Models of Selective Effects; 3.1 A Typical Adaptation Experiment; 3.2 A Simple Fatigue Model
3.3 The General Stiles Model3.4 Empirical Discrepancies in Spatial-Frequency Adaptation; 3.5 Some Stiles-Type Models Assuming Many Analyzers; 3.6 Even More General Fatigue Models; 3.7 Inhibition Plus Fatigue; 3.8 Inhibition Only; 3.9 Point-by-Point Fatigue (Afterimage) Explanations; 3.10 What Is the Function of Pattern-Selective Adaptation?; 3.11 Summary; Notes; Part III. SUMMATION; 4. Models for Far-Apart Values; 4.1 A Typical Summation Experiment; 4.2 An Additive Single-Analyzer Model; 4.3 A Nonadditive, Uniform, Single-Analyzer Model (a Single-Channel Model); 4.4 Multiple-Analyzers Model
4.5 A Single Nonuniform Channel (Example of Interaction Between Two Dimensions)4.6 Multiple-Analyzers Models Incorporating Variability; 4.7 High-Threshold Multiple-Analyzers Model; 4.8 Quick Pooling Model; 4.9 Quick Pooling Model Predictions for Summation of Far-Apart Components; 4.10 Summary; 4.11 Appendix. Derivation of Observable Quick Pooling Formulas; Notes; 5. Far-Apart Values on Spatial Dimensions; 5.1 Overview; 5.2 Far-Apart Orientations; 5.3 The Effect of Probability Summation Across Space on Spatial-Frequency and Orientation Models; 5.4 Summation of Far-Apart Spatial Positions
5.5 Summation Experiments on the Spatial-Extent Dimension5.6 Summation Experiments on the Spatial-Phase Dimension; 5.7 Summary; Notes; 6. Close Values on Spatial Dimensions; 6.1 Overview; 6.2 Two Additive, Deterministic Analyzers (the Naive Model); 6.3 More Sophisticated Multiple-Analyzers Models; 6.4 Summation of Close Spatial Frequencies; 6.5 Summation of Close Orientations; 6.6 Summation of Close Spatial Positions; 6.7 Summation of Close Spatial Frequencies-Interaction with Spatial Extent; 6.8 Summary; 6.9 Appendix. Details of Two Multiple-Mechanisms Models; Notes; Part IV. UNCERTAINTY
7. Extrinsic Uncertainty and Summation Revisited
Includes indexes.
Includes bibliography: p. 581-625.
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