Biological and Quantum Computing for Human Vision: Holonomic Models and Applications
Many-body interactions have been successfully described through models based on classical or quantum physics. More recently, some of the models have been related to cognitive science by researchers who are interested in describing brain activity through the use of artificial neural networks (ANNs). Biological and Quantum Computing for Human Vision: Holonomic Models and Applications presents an integrated model of human image processing up to conscious visual experience, based mainly on the Holonomic Brain Theory by Karl Pribram. This work researches possibilities for complementing neural models of early vision with the new preliminary quantum models of consciousness in order to construct a model of human image processing.
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Biological and Quantum Computing for Human Vision: Holonomic Models and Applications
Many-body interactions have been successfully described through models based on classical or quantum physics. More recently, some of the models have been related to cognitive science by researchers who are interested in describing brain activity through the use of artificial neural networks (ANNs). Biological and Quantum Computing for Human Vision: Holonomic Models and Applications presents an integrated model of human image processing up to conscious visual experience, based mainly on the Holonomic Brain Theory by Karl Pribram. This work researches possibilities for complementing neural models of early vision with the new preliminary quantum models of consciousness in order to construct a model of human image processing.
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Biological and Quantum Computing for Human Vision: Holonomic Models and Applications

Biological and Quantum Computing for Human Vision: Holonomic Models and Applications

Biological and Quantum Computing for Human Vision: Holonomic Models and Applications

Biological and Quantum Computing for Human Vision: Holonomic Models and Applications

Overview

Many-body interactions have been successfully described through models based on classical or quantum physics. More recently, some of the models have been related to cognitive science by researchers who are interested in describing brain activity through the use of artificial neural networks (ANNs). Biological and Quantum Computing for Human Vision: Holonomic Models and Applications presents an integrated model of human image processing up to conscious visual experience, based mainly on the Holonomic Brain Theory by Karl Pribram. This work researches possibilities for complementing neural models of early vision with the new preliminary quantum models of consciousness in order to construct a model of human image processing.

Product Details

ISBN-13: 9781615207855
Publisher: Medical Information Science Reference
Publication date: 11/30/2010
Pages: 316
Product dimensions: 7.20(w) x 10.10(h) x 1.00(d)

Table of Contents

Foreword viii

Summary x

Preface xiii

Acknowledgment xiv

Introduction xv

Section 1

Chapter 1 Introduction to Holonomic-Compatible Models for Vision 1

Starting Remarks 1

The Holonomic Model of Visual Perception 4

Search for Quantum Neural Substracts of Vision and Their Models 9

Quantum Associative Network 10

Trying to Integrate the Models 13

Endnotes 15

Chapter 2 Holonomic Brain Processes 19

General Scope of the Holonomic Brain Theory 19

Modeler's Discussion 23

Global View: Fourier and Gabor Transforms; "Informax Attractors" 25

Holonomic Theory of Vision 30

Endnotes 38

Chapter 3 Computational Information-Maximization Models 46

Maximal Preservation of Information ("Infomax") 46

ICA by Bell and Sejnowski 52

Sparseness Maximization by Olshausen and Field 55

Spatio-Temporal and Extended Infomax 59

Search for Biological Support of Infomax Models 62

Dendritic Field Computing 65

From Infomax-Based Image Processing to Secondary Associative Processing with Attractor Nets 66

Endnotes 67

Chapter 4 Images, Associations and Conscious Experience 73

Convolution, Correlation and Matrix-Processing 73

Attempt of an Integrated Model of Image Processing in VI and Beyond 74

Addition of Conscious Experience and Quantum Processes into Consideration 80

Non-Mathematical Description of Q.A.N. Model 82

Holographic Perceptual Out-to-Space Back Projection and Object-Image Match 85

Dendritic Holography-Like Image Processing 88

Microtubules, Coherent Subcellular and Quantum Processes, and Consciousness 91

Conscious Experience 94

Visual Conscious Experience 101

Endnotes 105

Chapter 5 Computer Simulations and Applications of Quantum Associative Network 112

Central Quantum Holographic Model 112

From Recognizing Images to Recognizing Objects 116

Orthogonalization Preprocessing 117

Bio-Computational Model of Object-Recognition 118

Quantum Hebbian Processing with Neurally Shaped Gabor Wavelets 120

Simulated Bio-Holography with Gabor Wavelets Encoding 121

Conclusion: Review of Book's Specific Contribution 127

Section 2

Chapter 6 Visual Processing as Described by Contemporary Main-Stream Neuroscience 131

Retina 131

Visual Pathway(s): L.G.N. and Magno-Parvo-Branches 134

To Striate Cortex and Beyond 136

Higher Visual Areas 138

General Neocortical Architecture and Connections 139

Selective Visual Attention 141

Elements of Active Visual Perception 144

Visual Memory 151

Origin of Selectivity for Visual Features: A Model 155

Global Retinotopic Mapping 159

The Role of Color-Information in Extraction of Edges and Contours 162

Dilemmas (Main-Stream Models vs. Holonomic Theory) 165

Endnotes 167

Chapter 7 Comparison of the Mathematical Formalism of Associative ANN and Quantum Theory 179

Main Neuro-Quantum Analogies and their Informational Significance 179

Discrepancies in Presented Analogies and Beyond 189

Additional Analogies 191

Consequences of Neuro-Quantum Parallels 196

Endnotes 197

Chapter 8 Derivation of Quantum Associative Network from Hopfield-Like ANN and HNeT 199

Connectionist Simulations Applied for Quantum Dynamics 199

Associative Neural Networks 200

Holographic Neural Technology (HNeT) 202

Quantum Associative Network 207

Example of Simulated Pattern Recognition 210

Endnotes 215

Chapter 9 Quantum Neural Information Processing 217

Chapter 10 Quantum Phase-Hebbian Image Processing 222

Chapter 11 Computational Models Relevant for Visual Cortex 229

ANN with Inhibitory Feedback-Loop Giving Informax Outputs 230

Network of Units with Coupled Oscillatory Activities, Embedded in Neuropil 230

Figure/Ground Segmentation by a Network of Phase-Coupled Oscillators 232

Endnotes 234

Appendix A Principal Component Analysis 235

Appendix B Kohonen's Model of Retinopic Mapping 239

Introduction to Perceptual Maps with Cardinal Neurons 239

Topologically-Correct Feature Mapping 242

Adaptive Learning by Error Minimization 243

Vector Quantization 248

Endnotes 250

Appendix C Important Mathematical Definitions 251

Appendix D Abbreviations and Neurological Adjectives 253

Compilation of References 255

About the Authors 291

Index 293

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