Biological neural networks hierarchical concept of brain function
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boston [u.a.]
Birkhäuser
1998
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| 100 | 1 | |a Baev, Konstantin V. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Biological neural networks |b hierarchical concept of brain function |c Konstantin V. Baev |
| 264 | 1 | |a Boston [u.a.] |b Birkhäuser |c 1998 | |
| 300 | |a XXXVII, 273 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 4 | |a Réseaux neuronaux (Neurobiologie) | |
| 650 | 4 | |a Automatism | |
| 650 | 4 | |a Brain |x physiology | |
| 650 | 4 | |a Learning |x physiology | |
| 650 | 4 | |a Models, Neurological | |
| 650 | 4 | |a Nerve Net |x physiology | |
| 650 | 4 | |a Neural networks (Neurobiology) | |
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Datensatz im Suchindex
| DE-BY-UBR_call_number | 01/22.X0814 |
|---|---|
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| DE-BY-UBR_location | 00 |
| DE-BY-UBR_media_number | 069022634241 |
| _version_ | 1822583754579771392 |
| adam_text | Contents
Preface ix
Acknowledgments x
Foreword by Alex Meystel xiii
Foreword by Karl A. Greene xxxv
Introduction 1
1 Limitations of Analytical Mechanistic Approaches to
Biological Neural Networks 7
1.1 Inborn Automatic Behaviors From the Point
of View of Classical Theory 10
1.1.1 A Brief Review of the Locomotor Behavior
Evolution in Animals 10
1.1.2 Initiation of Inborn Automatic Behaviors 12
1.1.3 The Problem of Organization of Central
Pattern Generators for Inborn Automatic
Behaviors 18
1.1.4 Afferent Correction of Central Pattern
Generators 35
1.1.5 Ontogenesis of Locomotor Function 38
1.1.6 Is the Formulation of the Generator Problem
Correct? 38
1.2 Learning from the Point of View of Classical Theory .... 41
1.2.1 Classical Conditioning of the Eyelid Closure
Response 44
2 The Control Theory Approach to Biological Neural
Networks 48
2.1 A Brief Historical Review of the Development of
Automatic Control Theory 48
vi Konstantin V. Baev
2.2 Basic Concepts of Control Theory 50
2.3 Computational Abilities of Biological Neural
Networks 56
2.4 Broadening the Concept of Automatism: Inborn
Automatisms and Acquired Habits 62
2.5 How Can Control Theory Concepts Be Applied to
Biological Neural Networks? 63
3 A Central Pattern Generator Includes A Model of
Controlled Object: An Experimental Proof 71
4 The Spinal Motor Optimal Control System 87
4.1 Sensory Information Processing in the Spinal
Motor Control System 92
4.2 The Essence of the Internal Model of the
Controlled Object 96
4.3 The Internal Representation of the Controlled
Object Phase State 96
4.4 The Principal Features of the Neural Organization
of Internal Representations of the Controlled Object
State and Its Model 97
4.5 Neural Mechanisms for Calculating the Most
Probable Current State of the Controlled Object 98
5 Generalizing the Concept of a Neural Optimal Control
System: A Generic Neural Optimal Control System 102
6 Learning in Artificial and Biological Neural Networks 110
6.1 The Problem of Learning in Neurocomputing 110
6.2 Basic Principles of Learning in Biological Neural
Networks 112
6.2.1 An Analogy: Brownian Motion of Particles
in the Presence of a Temperature Gradient 113
6.2.2 Change of Neuronal Transfer Function Due
to the Influence of Initiating Signals 114
6.2.3 Change of a Function Calculated by a
Neural Network 115
6.2.4 Basic Principles of Classical Conditioning 119
Contents vii
7 The Hierarchy of Neural Control Systems 126
8 Application of the Concept of Optimal Control Systems
to Inborn Motor Automatisms in Various Animal Species 132
8.1 The Principle of Motor Automatism Initiation 132
8.2 Invertebrate Central Pattern Generators from the
Perspective of the Optimal Control System 134
8.3 Vertebrate Central Pattern Generators from the
Perspective of the Optimal Control System 136
8.4 The Phenomenon of Entrainment of Central
Rhythms 137
8.5 A Generator is a Learning System! 139
9 The Stretch Reflex System 143
10 The Cerebellum 148
10.1 The Semantics of Cerebellar Inputs 148
10.2 How the Cerebellum Learns to Coordinate
Movements 150
11 The Skeletomotor Cortico Basal Ganglia Thalamocortical
Circuit 156
11.1 An Anatomical Survey of Cortico Basal
Ganglia Thalamocortical Circuits 156
11.2 What is Modeled by the Skeletomotor Basal
Ganglia Thalamocortical Circuit? 158
11.3 An Error Distribution System 161
11.4 Clinical Applications of the Theory 164
11.4.1 Parkinson s Disease 166
12 The Limbic System 175
12.1 Associated Automatisms 176
12.1.1 Automatisms Subordinated to the
Hypothalamus 176
12.1.2 Initiating Signals of the Hypothalamus 177
12.1.3 Cortical Automatisms Used by the Limbic
System 180
12.2 Specificity of Control Tasks: General
Considerations 180
viii Konstantin V. Baev
12.2.1 The Coordination Problem 181
12.2.2 Long Range Space and Time Orientation 182
12.2.3 From Conditioned Reflex to Operant
Learning 184
12.3 Functions of Different Limbic Structures 186
12.3.1 The Hypothalamus 187
12.3.2 The Hippocampus 187
12.3.3 The Cingulate Gyrus and its Cortico Basal
Ganglia Thalamocortical Loop 189
13 The Prefrontal Cortex 195
13.1 Means for Further Evolutionary Improvements 195
13.2 Prefrontal Cortico Basal Ganglia Thalamocortical
Loops 197
14 Conclusion 201
14.1 The Variety of Memory Mechanisms in the Brain 201
14.2 Non Neuronal Network Cellular and Molecular
Systems 202
14.2.1 The Immune System 203
14.2.2 Intracellular Systems 208
14.3 Evolution and Learning Processes 211
14.4 Self Applicability of the Theory and Its Application
to Other Sciences 215
14.5 Future of Neurobiology for Physicists 219
14.6 Artificial Intelligence and Future Neurocomputers 224
References 226
Appendix 243
1 The Main Properties of Sensory Information
Sources and Channels 243
2 Functioning of the Internal Model of the Controlled
Object 246
3 The Spinal Optimal Motor Control System as a
Neural Network 249
Abbreviations 254
Index 257
|
| any_adam_object | 1 |
| author | Baev, Konstantin V. |
| author_facet | Baev, Konstantin V. |
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| author_sort | Baev, Konstantin V. |
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| dewey-full | 573.8/6 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 573 - Specific physiological systems in animals |
| dewey-raw | 573.8/6 |
| dewey-search | 573.8/6 |
| dewey-sort | 3573.8 16 |
| dewey-tens | 570 - Biology |
| discipline | Biologie |
| format | Book |
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| id | DE-604.BV011657711 |
| illustrated | Illustrated |
| indexdate | 2024-12-23T14:37:32Z |
| institution | BVB |
| isbn | 0817638598 3764338598 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007859037 |
| oclc_num | 37362357 |
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| owner_facet | DE-355 DE-BY-UBR DE-12 DE-19 DE-BY-UBM |
| physical | XXXVII, 273 S. graph. Darst. |
| publishDate | 1998 |
| publishDateSearch | 1998 |
| publishDateSort | 1998 |
| publisher | Birkhäuser |
| record_format | marc |
| spellingShingle | Baev, Konstantin V. Biological neural networks hierarchical concept of brain function Réseaux neuronaux (Neurobiologie) Automatism Brain physiology Learning physiology Models, Neurological Nerve Net physiology Neural networks (Neurobiology) Modell (DE-588)4039798-1 gnd Nervennetz (DE-588)4041638-0 gnd Hierarchische Struktur (DE-588)4465281-1 gnd Hirnfunktion (DE-588)4159930-5 gnd |
| subject_GND | (DE-588)4039798-1 (DE-588)4041638-0 (DE-588)4465281-1 (DE-588)4159930-5 |
| title | Biological neural networks hierarchical concept of brain function |
| title_auth | Biological neural networks hierarchical concept of brain function |
| title_exact_search | Biological neural networks hierarchical concept of brain function |
| title_full | Biological neural networks hierarchical concept of brain function Konstantin V. Baev |
| title_fullStr | Biological neural networks hierarchical concept of brain function Konstantin V. Baev |
| title_full_unstemmed | Biological neural networks hierarchical concept of brain function Konstantin V. Baev |
| title_short | Biological neural networks |
| title_sort | biological neural networks hierarchical concept of brain function |
| title_sub | hierarchical concept of brain function |
| topic | Réseaux neuronaux (Neurobiologie) Automatism Brain physiology Learning physiology Models, Neurological Nerve Net physiology Neural networks (Neurobiology) Modell (DE-588)4039798-1 gnd Nervennetz (DE-588)4041638-0 gnd Hierarchische Struktur (DE-588)4465281-1 gnd Hirnfunktion (DE-588)4159930-5 gnd |
| topic_facet | Réseaux neuronaux (Neurobiologie) Automatism Brain physiology Learning physiology Models, Neurological Nerve Net physiology Neural networks (Neurobiology) Modell Nervennetz Hierarchische Struktur Hirnfunktion |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007859037&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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