Circuits in the Brain (eBook)

A Model of Shape Processing in the Primary Visual Cortex

Charles Legendy (Autor)

eBook Download: PDF

2009 | 2009
XXVI, 226 Seiten
Springer New York (Verlag)
978-0-387-88849-1 (ISBN)

Infos

Dr. Charles Legéndy's Circuits in the Brain: A Model of Shape Processing in the Primary Visual Cortex is published at a time marked by unprecedented advances in experimental brain research which are, however, not matched by similar advances in theoretical insight. For this reason, the timing is ideal for the appearance of Dr. Legéndy's book, which undertakes to derive certain global features of the brain directly from the neurons.

Circuits in the Brain, with its 'relational firing' model of shape processing, includes a step-by-step development of a set of multi-neuronal networks for transmitting visual relations, using a strategy believed to be equally applicable to many aspects of brain function other than vision. The book contains a number of testable predictions at the neuronal level, some believed to be accessible to the techniques which have recently become available.

With its novel approach and concrete references to anatomy and physiology, the monograph promises to open up entirely new avenues of brain research, and will be particularly useful to graduate students, academics, and researchers studying neuroscience and neurobiology. In addition, since Dr. Legéndy's book succeeds in achieving a clean logical presentation without mathematics, and uses a bare minimum of technical terminology, it may also be enjoyed by non-scientists intrigued by the intellectual challenge of the elegant devices applied inside our brain. The book is uniquely self-contained; with more than 120 annotated illustrations it goes into full detail in describing all functional and theoretical concepts on which it builds.

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Dr. Charles Legendy's Circuits in the Brain: A Model of Shape Processing in the Primary Visual Cortex is published at a time marked by unprecedented advances in experimental brain research which are, however, not matched by similar advances in theoretical insight. For this reason, the timing is ideal for the appearance of Dr. Legendy's book, which undertakes to derive certain global features of the brain directly from the neurons. Circuits in the Brain, with its "e;relational firing"e; model of shape processing, includes a step-by-step development of a set of multi-neuronal networks for transmitting visual relations, using a strategy believed to be equally applicable to many aspects of brain function other than vision. The book contains a number of testable predictions at the neuronal level, some believed to be accessible to the techniques which have recently become available. With its novel approach and concrete references to anatomy and physiology, the monograph promises to open up entirely new avenues of brain research, and will be particularly useful to graduate students, academics, and researchers studying neuroscience and neurobiology. In addition, since Dr. Legndy's book succeeds in achieving a clean logical presentation without mathematics, and uses a bare minimum of technical terminology, it may also be enjoyed by non-scientists intrigued by the intellectual challenge of the elegant devices applied inside our brain. The book is uniquely self-contained; with more than 120 annotated illustrations it goes into full detail in describing all functional and theoretical concepts on which it builds. About the Author:Dr. Charles Legndy holds a bachelors' degree in electrical engineering from Princeton and a PhD in physics from Cornell. He wrote his first papers in solid-state physics (helicons), then turned his attention to the theory of data processing in the brain, the subject of the present book. Over the years, in addition, he was involved in a number of projects in experimental brain research (electrophysiology), aerospace engineering, and computers. Dr. Legndy lives with his wife in New York City.

Inhalt

Preface 6
Contents 9
List of Figures 15
Introduction 19
Part I Concepts of Brain Theory 24
to 1 Lettvin's Challenge 25
to 2 Issues Concerning the Nature of Neuronal Response 27
2.1 Impressions Gained from Histograms and Raster Displays 27
2.2 Cortical Firing Should Be Nearly Periodic So Why Isnt It? 28
2.3 Sensitivity of Neurons to Synchronized Volleys of Spikes 30
2.4 Notes on Plastic Change at the Synaptic Level 31
to 3 ''Events'' in the Brain 33
3.1 The Brain Viewed as a Logic Network Without a System Clock 33
3.2 Looking for Surprising Events in the Neuronal Input Stream 34
3.3 Poisson Surprise as a Diagnostic Tool 35
3.4 Critique of Brain Models Relying on Average Spike Rates 36
3.5 The LTP Is Probably the Marking of Synapse Sets for Later Use 36
to 4 Cell Assemblies 39
4.1 Ignition 39
4.2 Synchronized One-Spike Ignitions 40
4.3 Ignitions and the Central Bins of Cross-Correlograms 40
4.4 Ignitions and Single-Unit Recording 41
4.5 Why Myelin Is Indispensable to Nervous Function? 42
to 5 Surprise, Statistical Inference, and Conceptual Notes 44
5.1 Spike Coincidence Interpreted in Terms of Surprise 44
5.2 Local Knowledge and Its Relation to Information 45
5.3 The Fundamental Law of Brain Theory 46
5.4 Parsing the Network into Localities 46
5.5 Brain Modeling Viewed as Reverse Engineering 47
to 6 A New Term: Ignitions Which ''Reach'' or ''Don''t Reach'' a Neuron 48
6.1 How Many Synapses Does It Take to Reach a Neuron? 48
6.2 Axons, Where They Arborize, Can Probably Contact Most Neurons 49
6.3 A Good Unit of Cortical Distance: The Width of a Column 51
6.4 Axonal Branching Near the Cell Body 52
6.5 Retinotopic Mapping 52
6.6 Axons Which Confine Their Branching to a Few Columns 53
to 7 Confirmation Loops, Powered by Self-Ignitions 55
7.1 The Principle of Overwhelming Odds 55
7.2 Prime Mover Networks at the Sending End of Surprising Signals 55
7.3 Confirmation Loops and the Classical Reverberations 57
to 8 Communicating ''Relatedness'' Through Time-Linked Ignitions 59
8.1 Time-Linked Ignitions Viewed as Sentences 59
8.2 Joining Sentences on Shared Nouns 60
to 9 Relational Firing: Broadcasting a Shape Through Time-Linked Ignitions 62
9.1 Labeled Lines: The Messenger Is the Message 62
9.2 Direction-Coded Cells 63
9.3 Relational Firing: Two Cell Groups Broadcasting a Relation 64
9.4 Visual Sentences Conveying that Two Sides Meet in One Point 66
9.5 Kernel Cells, Used in Joining Co-ignitions on Shared Points 67
9.6 Visual Sentences Communicating a Triangular Shape 69
9.7 Contour Cells and Direction-Coded Cells 70
9.8 Broadcasting More Complex Shapes 73
9.9 The Role of Retinotopy and Connectivity 76
9.10 Confirmation Loops and the Epochs on High Poisson Surprise 77
9.11 3D Extension of Polygon Graphics 78
9.12 Distributed Knowledge 78
Part II Contour Strings and the Contour Wave 79
to 10 Enter the Contour String 80
10.1 The Issue of Enabling Communication Between Parts of an Image 80
10.2 Cells Which Link Up to Pass Waves When Co-stimulated 80
10.3 -1Ignition on the Contour Moves Like a Wave (Contour Wave) 81
10.4 Seeing Viewed as Short-Term Learning 82
10.5 Only the Simple Cell Is Suitable for Conducting the Contour Waves 82
10.6 The Need for Drome-Selectivity in Simple Cells 82
10.7 The Problem of Converting Facts into Events 83
10.8 The Contour String as a Prime Mover 84
10.9 The Contour String as Representation of a Gestalt 84
to 11 Drift of the Retinal Image 87
11.1 Tracking the Nouns Used in Joining Sentences 87
11.2 The Word Fixation Is a Misnomer 88
11.3 A Period of Fixation Is a Period of Tracking 88
to 12 Theory of the Simple Cell 90
12.1 Simple Cells, When Detecting LGN Input, Must Link Up Fast 90
12.2 Warm-Up of Simple Cells by the Approaching Contour Wave 90
12.3 Cross-Potentiation : One Synapse Pool Changing the Effect of Another 91
12.4 The Graphical Notation of Neuron Sets and Synapse Sets 92
12.5 The Preparation of Simple Cells for Their Role in Contour Waves 94
to 13 Theory of the Complex Cell 100
13.1 Tracking 100
13.2 Tracking Based on Overlap: Dynamically Marked Synapses 101
13.3 Dynamic Marking Shown in Drawings as Just Marking 102
13.4 The Trick of Simple Cells Feeding into Complex Cells 103
13.5 Simple and Complex Cell Responses Are All Contour Wave Responses 105
13.6 How the Complex Cell Works 105
to 14 Corner Processing: Theory of the Hypercomplex Cell 108
14.1 Propagation of Contour Waves Toward and Away from Corners 108
14.2 Corner-Supporting Simple (CS Simple) Cells 108
14.3 Hypercomplex Cells 113
14.4 Comparing Hypercomplex and CS Simple Cells 113
Part III Nodes, Links, Bridgeheads 115
to 15 Nodes on Contour Strings 116
15.1 The Problem of Slow Propagation 116
15.2 The Stria of Gennari 116
15.3 Speed-Up by Means of Nodes Linked by Gennari Fibers 117
15.4 Nodes Viewed as Representing Points 117
15.5 A Note on the Fiber Requirement of Visual Integration 118
15.6 The Placement of Nodes on a Contour 119
15.7 A Link Between Nodes Has a Bridgehead on Each Node 120
to 16 Custom-Made Unstable Networks Made to Support Tracking 122
16.1 Self-Igniting Networks Which Continually Gain and Lose Cells 122
16.2 Active Linkage: Two Bridgeheads Repeatedly Co-igniting 123
16.3 Detecting When a Link Becomes Weak 124
16.4 The Linkage Between Tracking, Metric Relations, and Long-Term Storage 128
16.5 Tracking a Contour Whose Shape Changes 129
16.6 Restoring a Weakened Link 130
to 17 Why Is the Drifting Retinal Image Helpful in Perception? 133
17.1 The Growth of Nodes in the Course of Contour Drift 133
17.2 Kernel Cells in Multi-column Nodes 138
to 18 The Maintenance of Moving Nodes and Bridgeheads 140
18.1 Adding New Neurons to a Drifting Node 140
18.2 Spread of a Bridgehead Sideways, Along the Contour 144
Part IV Firing Games and the Integration of Contours 149
to 19 Making the First Links by Crawling Along a Contour String 150
19.1 Outline of the Continuity Detection and Contour Linkup 150
19.1.1 Nodes and Their Initial Ignitions 151
19.1.2 The Cells as Individuals Cannot See the Whole Picture 151
19.1.3 How a ''Grand Design'' Enables Cells to Convey More Than They Know 152
19.1.4 Localities Monitoring the Moving Wave Via Long Axons 152
19.1.5 The Smallest Cell Group Able to Trade Knowledge: The Node 153
19.1.6 Monitoring Single Contour Waves in Isolation: The ''Tracer Wave'' 154
19.1.7 Preventing Extra Waves from Being Traced: The ''Second Enable'' 155
19.1.8 Satisfying the Surprise Requirement of ''Second Enable'': Warmup Runs 155
19.1.9 Tracer Waves Continuous with an ''Arrival Volley'' from the Next Node 156
19.1.10 How Can the Base Node Recognize the Arrival Volleys? 156
19.1.11 Saving the Detected Continuity in the Form of Hardware 157
19.1.12 Node A Knows that the Reaching Is Bidirectional So Does Node B
19.1.13 Linkup and Active Link Operation 158
19.2 Operating Modes of Neurons 159
19.3 Firing Games: Goal-Directed Organization Without a Leader 160
19.4 Directional Specificity of Contour Cells: R-cells and L-cells 161
19.5 A Note on the Drawings Describing Contour Linkup 161
19.6 Synaptic Interactions During Tracer Runs and Linkup 165
19.7 Continuity Detection from the Standpoint of the Base Cells 170
19.8 Understudy Processing of Cells Before They Join a Node 173
19.9 Phases of a Linkup, with Each Phase hammered in by Repetitions 174
19.10 Suppressing Tracer Waves Beyond the First Node They Encounter 180
19.11 Recognition of Crosstalk Between Two Contours 180
to 20 Using Existing Links to Make New Links on the Same Contour 184
20.1 Outline of Using Two Links to Make a Third Link on the Same Contour 184
20.1.1 Relation ''A on Same Contour as B'' is Transitive But There is a Catch
20.1.2 Linkup of Two Nodes Must Start from a Third, with Links to Both 185
20.1.3 Three-Node Ignitions 185
20.1.4 Making the Triple Ignitions Reach the Satellite Nodes 186
20.1.5 The Issue of Limiting the Search Volleys to a Range of Directions 186
20.1.6 How Do Nodes A and C Know that They Are Supposed to Link Up? 187
20.1.7 The Beginning of the Bridgeheads of an A--C Link 187
20.1.8 The Challenge of Making the Bridgeheads Ignitable 188
20.1.9 Gradual Growth of the New Bridgeheads 188
20.1.10 The Cessation of Omnidirectional Volleys 189
20.1.11 Setting Up Mutual Excitation Between Nodes A and C 190
20.1.12 The Next Step Is to Separate the A--B Link and B--C Link Again 190
20.1.13 How Do the Bridgeheads in B Know to Undo Their Linkage? 190
20.1.14 Restoring the A--B Link and B--C Link 191
20.1.15 Why Not Just Start a Free-for-All of Echolocation? 192
20.2 Extending a Long Link to the Next Node on a Contour 192
20.2.1 Node-Level Description of the Linkup Step 193
20.2.2 Description of the Linkup Step in More Detail 196
to 21 Completing a Triangle of Links 208
21.1 Closing a Triangle 208
21.2 How to Spot Open Triangles: The Three-Element Problem 210
to 22 All-to-All Linkup on Smaller Shapes, Utilizing Chain Ignitions 216
22.1 Indiscriminate Linkup of All Nodes 216
Closing Remarks 219
References 220
Index 226

Produkt-Details

• Erscheint lt. Verlag: 20.4.2009
• Zusatzinfo: XXVI, 226 p. 100 illus.
• Verlagsort: New York
• Sprache: englisch
• Themenwelt: Geisteswissenschaften ► Geschichte
• Themenwelt: Geisteswissenschaften ► Philosophie ► Allgemeines / Lexika
• Themenwelt: Medizin / Pharmazie ► Medizinische Fachgebiete ► Neurologie
• Themenwelt: Medizin / Pharmazie ► Studium
• Themenwelt: Naturwissenschaften ► Biologie ► Humanbiologie
• Themenwelt: Naturwissenschaften ► Biologie ► Zoologie
• Themenwelt: Naturwissenschaften ► Physik / Astronomie
• Themenwelt: Technik
• Schlagworte: anatomy • contour stringcon • contour wave • Cortex • Electrical Engineering • firing game • Legendy • linear optimization • Model • Neurobiology • Neuron • neurons • perception • Physiology
• ISBN-10: 0-387-88849-7 / 0387888497
• ISBN-13: 978-0-387-88849-1 / 9780387888491