Grossberg The Adaptive Brain II

Vision, Speech, Language, and Motor Control
1. Auflage 2013
ISBN: 978-1-4832-9270-0
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 532 Seiten, Web PDF

The Adaptive Brain, II: Vision, Speech, Language, and Motor Control focuses on a unified theoretical analysis and predictions of important psychological and neurological data that illustrate the development of a true theory of mind and brain. The publication first elaborates on the quantized geometry of visual space and neural dynamics of form perception. Discussions focus on reflectance rivalry and spatial frequency detection, figure-ground separation by filling-in barriers, and disinhibitory propagation of functional scaling from boundaries to interiors. The text then takes a look at neural dynamics of perceptual grouping and brightness perception. Topics include simulation of a parametric binocular brightness study, smoothly varying luminance contours versus steps of luminance change, macrocircuit of processing stages, paradoxical percepts as probes of adaptive processes, and analysis of the Beck theory of textural segmentation. The book examines the neural dynamics of speech and language coding and word recognition and recall, including automatic activation and limited-capacity attention, a macrocircuit for the self-organization of recognition and recall, role of intra-list restructuring arid contextual associations, and temporal order information across item representations. The manuscript is a vital source of data for scientists and researchers interested in the development of a true theory of mind and brain.

Autoren/Hrsg.

Grossberg, Stephen

Inhaltsverzeichnis

1;Front Cover;1
2;The Adaptive Brain II: Vision, Speech, Language, and Motor Control;4
3;Copyright Psge;5
4;Table of Contents;11
5;Dedication;6
6;EDITORIAL PREFACE;8
7;Chapter 1. THE QUANTIZED GEOMETRY OF VISUAL SPACE: THE COHERENT COMPUTATION OF DEPTH, FORM, AND LIGHTNESS;20
7.1;Preface;20
8;THE QUANTIZED GEOMETRY OF VISUAL SPACE: THE COHERENT COMPUTATION OF DEPTH, FORM, AND LIGHTNESS;22
8.1;Abstract;22
8.2;1. Introduction: The Abundance of Visual Models;23
8.3;2. The Quantized Geometry of Visual Space;23
8.4;3. The Need for Theories Which Match the Data's Coherence;24
8.5;4. Some Influences of Perceived Depth on Perceived Size;25
8.6;5. Some Monocular Constraints on Size Perception;25
8.7;6. Multiple Scales in Figure and Ground: Simultaneous Fusion and Rivalry;26
8.8;7. Binocular Matching, Competitive Feedback, and Monocular Self-Matching;28
8.9;8. Against the Keplerian View: Scale-Sensitive Fusion and Rivalry;30
8.10;9. Local versus Global Spatial Scales;31
8.11;11. Some Influences of Perceived Depth and Form on Perceived Brightness;32
8.12;12. Some Influences of Perceived Brightness on Perceived Depth;32
8.13;13. The Binocular Mixing of Monocular Brightnesses;35
8.14;14. The Insufficiency of Disparity Computations;35
8.15;15. The Insufficiency of Fourier Models;37
8.16;16. The Insufficiency of Linear Feedforward Theories;38
8.17;17. The Filling-In Dilemma: To Have Your Edge and Fill-in Too;39
8.18;18. Edges and Fixations: The Ambiguity of Statistically Uniform Regions;40
8.19;19. Object Permanence and Multiple Spatial Scales;42
8.20;20. Cooperative versus Competitive Binocular Interactions;42
8.21;21. Reflectance Processing, Weber Law Modulation, and Adaptation Level in Feedforward Shunting Competitive Networks;43
8.22;22. Pattern Matching and Multidimensional Scaling Without a Metric;46
8.23;23. Weber Law and Shift Property Without Logarithms;47
8.24;24. Edge, Spatial Frequency, and Reflectance Processing by the Receptive Fields of Distance-Dependent Feedforward Networks;49
8.25;25. Statistical Analysis by Structural Scales: Edges With Scaling and Reflectance Properties Preserved;52
8.26;26. Correlation of Monocular Scaling With Binocular Fusion;53
8.27;27. Noise Suppression in Feedback Competitive Networks;55
8.28;28. Sigmoid Feedback Signals and Tuning;55
8.29;29. The Interdependence of Contrast Enhancement and Tuning;60
8.30;30. Normalization and Multistability in a Feedback Competitive Network: A Limited Capacity Short Term Memory System;60
8.31;31. Propagation of Normalized Disinhibitory Cues;61
8.32;32. Structural versus Functional Scales;61
8.33;33. Disinhibitory Propagation of Functional Scaling From Boundaries to Interiors;63
8.34;34. Quantization of Functional Scales: Hysteresis and Uncertainty;63
8.35;35. Phantoms;64
8.36;36. Functional Length and Emmert's Law;65
8.37;37. Functional Lightness and the Cornsweet Effect;66
8.38;38. The Monocular Length-Luminance Effect;66
8.39;39. Spreading FIRE: Pooled Binocular Edges, False Matches, Allelotropia, Binocular Brightness Summation, and Binocular Length Scaling;67
8.40;40. Figure-Ground Separation by Filling-in Barriers;75
8.41;41. The Principle of Scale Equivalence and the Curvature of Activity-Scale Correlations: Fechner's Paradox, Equidistance Tendency, and Depth Without Disparity;75
8.42;42. Reflectance Rivalry and Spatial Frequency Detection;77
8.43;43. Resonance in a Feedback Dipole Field: Binocular Development and Figure-Ground Completion;78
8.44;44. Binocular Rivalry;81
8.45;45. Concluding Remarks About Filling-In and Quantization;82
8.46;APPENDIX;83
8.47;REFERENCES;86
9;Chapter 2. NEURAL DYNAMICS OF FORM PERCEPTION: BOUNDARY COMPLETION, ILLUSORY FIGURES, AND NEON COLOR SPREADING;99
9.1;Preface;99
10;NEURAL DYNAMICS OF FORM PERCEPTION: BOUNDARY COMPLETION, ILLUSORY FIGURES, AND NEON COLOR SPREADING;101
10.1;Abstract;101
10.2;1. Illusions as a Probe of Adaptive Visual Mechanisms;102
10.3;2. From Noisy Retina to Coherent Percept;102
10.4;3. Boundary Contour System and Feature Contour System;104
10.5;4. Boundary Contours and Boundary Completion;104
10.6;5. Feature Contours and Diffusive Filling-In;108
10.7;6. Macrocircuit of Processing Stages;110
10.8;7. Neon Color Spreading and Complementary Color Induction;110
10.9;8. Contrast, Assimilation, and Grouping;116
10.10;9. Boundary Completion: Positive Feedback Between Local Competition and Long-Range Cooperation of Oriented Boundary Contour Segments;118
10.11;10. Boundary Completion as a Statistical Process: Textural Grouping and Object Recognition;124
10.12;11. Perpendicular versus Parallel Contour Completion;124
10.13;12. Spatial Scales and Brightness Contrast;127
10.14;13. Boundary-Feature Trade-Off: Orientational Uncertainty and Perpendicular End Cutting;128
10.15;14. Induction of "Real" Contours Using "Illusory" Contour Mechanisms;131
10.16;15. Gated Dipole Fields;132
10.17;16. Boundary Completion: Oriented Cooperation Among Multiple Spatial Scales;133
10.18;17. Computer Simulations;135
10.19;18. Brightness Paradoxes and the Land Retinex Theory;140
10.20;19. Related Data and Concepts About Illusory Contours;146
10.21;20. Cortical Data and Predictions;146
10.22;21. Concluding Remarks;148
10.23;APPENDIX: Dynamics of Boundary Formation;153
10.24;REFERENCES;157
11;Chapter 3. NEURAL DYNAMICS OF PERCEPTUAL GROUPING: TEXTURES, BOUNDARIES, AND EMERGENT SEGMENTATIONS;162
11.1;Preface;162
12;NEURAL DYNAMICS OF PERCEPTUAL GROUPING: TEXTURES, BOUNDARIES, AND EMERGENT SEGMENTATIONS;163
12.1;Abstract;163
12.2;1. Introduction: Towards A Universal Set of Rules for Perceptual Grouping;164
12.3;2. The Role of Illusory Contours;166
12.4;3. Discounting the Illuminant: Color Edges and Featural Filling-in;168
12.5;4. Featural Filling-in Over Stabilized Scenic Edges;168
12.6;5. Different Rules for Boundary Contours and Feature Contours;170
12.7;6. Boundary-Feature Trade-Off: Every Line End Is Illusory;172
12.8;7. Parallel Induction by Edges versus Perpendicular Induction by Line Ends;173
12.9;8. Boundary Completion via Cooperative-Competitive Feedback Signaling: CC Loops and the Statistics of Grouping;177
12.10;9. Form Perception versus Object Recognition: Invisible but Potent Boundaries
;181
12.11;10. Analysis of the Beck Theory of Textural Segmentation: Invisible Colinear Cooperation;182
12.12;11. The Primacy of Slope;184
12.13;12. Statistical Properties of Oriented Receptive Fields: OC Filters;184
12.14;13. Competition Between Perpendicular Subjective Contours;186
12.15;14. Multiple Distance-Dependent Boundary Contour Interactions: Explaining Gestalt Rules;189
12.16;15. Image Contrasts and Neon Color Spreading;192
12.17;16. Computer Simulations of Perceptual Grouping;196
12.18;17. On-Line Statistical Decision Theory and Stochastic Relaxation;199
12.19;18. Correlations Which Cannot Be Perceived: Simple Cells, Complex Cells, and Cooperation;206
12.20;19. Border Locking: The Café Wall Illusion;208
12.21;20. Boundary Contour System Stages: Predictions About Cortical Architectures;212
12.22;21. Concluding Remarks: Universality of the Boundary Contour System;217
12.23;APPENDIX: Boundary Contour System Equations;221
12.24;REFERENCES;226
13;Chapter 4. NEURAL DYNAMICS OF BRIGHTNESS PERCEPTION: FEATURES, BOUNDARIES, DIFFUSION, AND RESONANCE;230
13.1;Preface;230
14;NEURAL DYNAMICS OF BRIGHTNESS PERCEPTION: FEATURES, BOUNDARIES, DIFFUSION, AND RESONANCE;231
14.1;Abstract;231
14.2;1. Paradoxical Percepts as Probes of Adaptive Processes;232
14.3;2. The Boundary-Contour System and the Feature-Contour System;234
14.4;3. Boundary Contours and Boundary Completion;234
14.5;4. Feature Contours and Diffusive Filling-In;238
14.6;5. Macrocircuit of Processing Stages;239
14.7;6. FIRE: Resonant Lifting of Preperceptual Data into a Form-in-Depth Percept;241
14.8;7. Binocular Rivalry, Stabilized lmages, and the Ganzfeld;243
14.9;8. The Interplay of Controlled and Automatic Processes;244
14.10;9. Craik-O'Brien Luminance Profiles and Multiple Step Illusions;244
14.11;10. Smoothly Varying Luminance Contours versus Steps of Luminance Change
;248
14.12;12. Simulations of FIRE;258
14.13;13. Fechner's Paradox;262
14.14;14. Binocular Brightness Averaging and Summation;266
14.15;15. Simulation of a Parametric Binocular Brightness Study;266
14.16;16. Concluding Remarks;270
14.17;APPENDIX A;277
14.18;APPENDIX B;282
15;Chapter 5. ADAPTATION AND TRANSMITTER GATING IN VERTEBRATE PHOTORECEPTORS;290
15.1;Preface;290
16;ADAPTATION AND TRANSMITTER GATING IN VERTEBRATE PHOTORECEPTORS;292
16.1;Abstract;292
16.2;1. Introduction;292
16.3;2. Transmitters as Gates;294
16.4;3. Intracellular Adaptation and Overshoot;295
16.5;4. Monotonie Increments and Nonmonotonic Overshoots to Flashes on Variable Background;298
16.6;5. Miniaturized Transducers and Enzymatic Activation of Transmitter Production;300
16.7;6. Turn-Around of Potential Peaks at High Background Intensities;302
16.8;7. Double Flash Experiments;303
16.9;8. Antagonistic Rebound by an Intracellular Dipole: Rebound Hyperpolarization Due to Current Offset;306
16.10;10. "Extra" Slow Conductance During Overshoot and Double Flash Experiments;311
16.11;11. Shift Property and its Relationship to Enzymatic Modulation;312
16.12;12. Rebound Hyperpolarization, Antagonistic Rebound, and Input Doubling;313
16.13;13. Transmitter Mobilization;315
16.14;14. Quantitative Analysis of Models;319
16.15;15. Comparison with the Baylor, Hodgkin, Lamb Model;324
16.16;16. Conclusion;327
16.17;ADDENDUM;327
16.18;REFERENCES;328
17;Chapter 6. THE ADAPTIVE SELF-ORGANIZATION OF SERIAL ORDER IN BEHAVIOR: SPEECH, LANGUAGE, AND MOTOR CONTROL;330
17.1;Preface;330
18;THE ADAPTIVE SELF-ORGANIZATION OF SERIAL ORDER IN BEHAVIOR: SPEECH, LANGUAGE, AND MOTOR CONTROL;332
18.1;1. Introduction: Principles of Self-Organization in Models of Serial Order: Performance Models versus Self-Organizing Models;332
18.2;2. Models of Lateral Inhibition, Temporal Order, Letter Recognition, Spreading Activation, Associative Learning, Categorical Perception, and Memory Search: Some Problem Areas;333
18.3;3. Associative Learning by Neural Networks: Interactions Between STM and LTM;339
18.4;4. LTM Unit is a Spatial Pattern: Sampling and Factorization;343
18.5;5. Outstar Learning: Factorizing Coherent Patterns From Chaotic Activity;344
18.6;6. Sensory Expectations, Motor Synergies, and Temporal Order Information;347
18.7;7. Ritualistic Learning of Serial Behavior: Avalanches;348
18.8;8. Decoupling Order and Rhythm: Nonspecific Arousal as a Velocity Command;351
18.9;9. Reaction Time and Performance Speed-Up;351
18.10;10. Hierarchical Chunking and the Learning of Serial Order;354
18.11;11. Self-Organization of Plans: The Goal Paradox;354
18.12;12. Temporal Order Information in LTM;357
18.13;13. Read-Out and Self-Inhibition of Ordered STM Traces;357
18.14;14. The Problem of STM LTM Order Reversal;358
18.15;15. Serial Learning;362
18.16;16. Rhythm Generators and Rehearsal Waves;363
18.17;17. Shunting Competitive Dynamics in Pattern Processing and STM: Automatic Self-Tuning by Parallel Interactions;364
18.18;18. Choice, Contrast Enhancement , Limited STM Capacity, and Quenching Threshold;365
18.19;19. Limited Capacity Without a Buffer: Automaticity versus Competition;368
18.20;20. Hill Climbing and the Rich Get Richer;369
18.21;21. Instar Learning: Adaptive Filtering and Chunking;370
18.22;22. Spatial Gradients, Stimulus Generalization, and Categorical Perception;372
18.23;23. The Progressive Sharpening of Memory: Tuning Prewired Perceptual Categories;373
18.24;24. Stabilizing the Coding of Large Vocabularies: Top-Down Expectanies and STM Reset by Unexpected Events;375
18.25;25. Expectancy Matching and Adaptive Resonance;378
18.26;26. The Processing of Novel Events: Pattern Completion versus Search of Associative Memory;378
18.27;27. Recognition, Automaticity, Primes, and Capacity;380
18.28;28. Anchors, Auditory Contrast, and Selective Adaptation;382
18.29;29. Training of Attentional Set and Perceptual Categories;384
18.30;30. Circular Reactions, Babbling, and the Development of Auditory-Articulatory Space;384
18.31;31. Analysis-By-Synthesis and the Imitation of Novel Events;385
18.32;32. A Moving Picture of Continuously Interpolated Terminal Motor Maps: Coarticulation and Articulatory Undershoot;387
18.33;33. A Context-Sensitive STM Code for Event Sequences;388
18.34;34. Stable Unitization and Temporal Order Information in STM: The LTM Invariance Principle;388
18.35;35. Transient Memory Span, Grouping, and Intensity-Time Tradeoffs;393
18.36;36. Backward Effects and Effects of Rate on Recall Order;393
18.37;37. Seeking the Most Predictive Representation: All Letters and Words are Lists;394
18.38;38. Spatial Frequency Analysis of Temporal Patterns by a Masking Field: Word Length and Superiority;395
18.39;39. The Temporal Chunking Problem;395
18.40;40. The Masking Field: Joining Temporal Order to Differential Masking via an Adaptive Filter;396
18.41;41. The Principle of Self-Similarity and the Magic Number 7;397
18.42;42. Developmental Equilibration of the Adaptive Filter and its Target Masking Field;398
18.43;43. The Self-Similar Growth Rule and the Opposites Attract Rule;399
18.44;44. Automatic Parsing, Learned Superiority Effects, and Serial Position Effects During Pattern Completion;401
18.45;45. Gray Chips or Great Ships?;403
18.46;46. Sensory Recognition versus Motor Recall: Network Lesions and Amnesias;403
18.47;47. Four Types of Rhythm: Their Reaction Times and Arousal Sources;404
18.48;48. Concluding Remarks;406
18.49;REFERENCES;410
19;Chapter 7. NEURAL DYNAMICS OF WORD RECOGNITION AND RECALL: ATTENTIONAL PRIMING, LEARNING, AND RESONANCE;420
19.1;Preface;420
20;NEURAL DYNAMICS OF WORD RECOGNITION AND RECALL: ATTENTIONAL PRIMING, LEARNING, AND RESONANCE;422
20.1;Abstract;422
20.2;1. Introduction;423
20.3;2. Logogens and Embedding Fields;425
20.4;3. Verification by Serial Search;426
20.5;4. Automatic Activation and Limited-Capacity Attention;428
20.6;5. Interactive Activation and Parallel Access;429
20.7;6. The View from Adaptive Resonance Theory;430
20.8;7. Elements of the Microtheory: Tuning, Categories, Matching, and Resonance;431
20.9;8. Counting Stages: Resonant Equilibration as Verification and Attention;438
20.10;9. Attentional Gain Control Versus Attentional Priming: The 2/3 Rule;439
20.11;10. A Macrocircuit for the Self-Organization of Recognition and Recall;444
20.12;11. The Schvaneveldt-McDonald Lexical Decision Experiments: Template Feedback and List-Item Error Trade-Off;449
20.13;12. Word Frequency Effects in Recognition and Recall;458
20.14;13. Analysis of the Underwood and Freund Theory;460
20.15;14. Analysis of the Mandler Theory;461
20.16;15. The Role of Intra-List Restructuring and Contextual Associations;464
20.17;16. An Explanation of Recognition and Recall Differences;465
20.18;17. Concluding Remarks;467
20.19;REFERENCES;469
21;Chapter 8. NEURAL DYNAMICS OF SPEECH AND LANGUAGE CODING: DEVELOPMENTAL PROGRAMS, PERCEPTUAL GROUPING, AND COMPETITION FOR SHORT TERM MEMORY;475
21.1;Preface;475
22;NEURAL DYNAMICS OF SPEECH AND LANGUAGE CODING: DEVELOPMENTAL PROGRAMS, PERCEPTUAL GROUPING, AND COMPETITION FOR SHORT TERM MEMORY;476
22.1;Abstract;476
22.2;1. Introduction: Context - Sensitivity of Self-Organizing Speech and Language Units;477
22.3;2. Developmental Rules Imply Cognitive Rules as Emergent Properties of Neural Network Interactions;478
22.4;3. A Macrocircuit for the Self-Organization of Recognition and Recall;478
22.5;4. Masking Fields;480
22.6;5. The Temporal Chunking Problem: Seeking the Most Predictive Representation;480
22.7;6. The Word Length Effect;481
22.8;7. All Letters Are Sublists: Which Computational Units Can Self-Organize?;481
22.9;8. Self-Organization of Auditory-Motor Features, Items, and Synergies;482
22.10;9. Temporal Order Information Across Item Representations: The Spatial Recoding of Temporal Order;484
22.11;10. The LTM Invariance Principle;484
22.12;11. The Emergence of Complex Speech and Language Units;485
22.13;12. List Chunks, Recognition, and Recall;485
22.14;13. The Design of a Masking Field: Spatial Frequency Analysis of Item-Order Information;486
22.15;14. Development of a Masking Field: Random Growth and Self-Similar Growth;488
22.16;15. Activity - Contingent Self-Similar Cell Growth;489
22.17;16. Sensitivity to Multiple Scales and Intrascale Variations;492
22.18;17. Hypothesis Formation, Anticipation, Evidence, and Prediction;492
22.19;18. Computer Simulations;494
22.20;19. Shunting On - Center Off - Surround Networks;500
22.21;20. Mass Action Interaction Rules;508
22.22;21. Self-Similar Growth Within List Nodes;509
22.23;22. Conservation of Synaptic Sites;509
22.24;23. Random Growth from Item Nodes to List Nodes;510
22.25;24. Self-Similar Competitive Growth Between List Nodes;511
22.26;25. Contrast Enhancement by Sigmoid Signal Functions;511
22.27;26. Concluding Remarks: Grouping and Recognition Without Algorithms or Search;512
22.28;APPENDIX;513
22.29;REFERENCES;515
23;AUTHOR INDEX;518
24;SUBJECT INDEX;524