Neural control engineering: the emerging intersection between control theory and neuroscience
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge, MA
MIT Press
2012
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| Series: | Computational neuroscience series
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XVI, 361 S. Ill., graph. Darst. |
| ISBN: | 9780262015370 |
Staff View
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| 245 | 1 | 0 | |a Neural control engineering |b the emerging intersection between control theory and neuroscience |c Steven J. Schiff |
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Record in the Search Index
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| adam_text | Titel: Neural control engineering
Autor: Schiff, Steven J.
Jahr: 2012
Contents
Series Foreword xi
Preface xiii
Introduction 1
1.1 Overview 1
1.2 A Motivational Example 3
1.3 Least Squares 10
1.4 Expectation and Covariance 14
1.5 Recursive Least Squares 17
1.6 It s a Bayesian World 19
Kaiman Filtering 25
2.1 Linear Kaiman Filtering 25
2.2 Nonlinear Kaiman Filtering 29
2.3 Why Not Neuroscience? 37
The Hodgkin-Huxley Equations 41
3.1 Pre-Hodgkin and Huxley 41
3.2 Hodgkin and Huxley and Colleagues 43
3.3 Hodgkin and Huxley 49
Simplified Neuronal Models 79
4.1 The Van der Pol Equations 79
4.2 Frequency Demultiplication 82
4.3 Bonhoeffer and the Passivation of Iron 82
4.4 Fitzhugh and Neural Dynamics 86
4.5 Nagumo s Electrical Circuit 91
4.6 Rinzel s Reduction 91
4.7 Simplified Models and Control 94
vjji Contents
Bridging from Kaiman to Neuron 97
5.1 Introduction 97
5.2 Variables and Parameters 99
5.3 Tracking the Lorenz System 101
5.4 Parameter Tracking 104
5.5 The Fitzhugh-Nagumo Equations 106
Spatiotemporal Cortical Dynamics-The Wilson Cowan
Equations 115
6.1 Before Wilson and Cowan 115
6.2 Wilson and Cowan before 1973 116
6.3 Wilson and Cowan during 1973 126
6.4 Wilson and Cowan after 1973 131
6.5 Spirals, Rings, and Chaotic Waves in Brain 133
6.6 Wilson-Cowan in a Control Framework 139
Empirical Models 153
7.1 Overview 153
7.2 The Second Rehnquist Court 156
7.3 The Geometry of Singular Value Decomposition 161
7.4 Static Image Decomposition 164
7.5 Dynamic Spatiotemporal Image Analysis 166
7.6 Spatiotemporal Brain Dynamics 168
Model Inadequacy 183
8.1 Introduction 183
8.2 The Philosophy of Model Inadequacy 185
8.3 The Mapping Paradigm-Initial Conditions 186
8.4 The Transformation Paradigm 190
8.5 Generalized Synchrony 195
8.6 Data Assimilation as Synchronization of Truth and Model 199
8.7 The Consensus Set 208
Brain-Machine Interfaces 215
9.1 Overview 215
9.2 The Brain 215
9.3 In the Beginning 216
9.4 After the Beginning 219
9.5 Beyond Bins-Moving from Rates to Points in Time 224
9.6 Back from the Future 227
9.7 When Bad Models Happen to Good Monkeys 232
9.8 Toward the Future 234
Contents
10 Parkinson s Disease 237
10.1 Overview 237
10.2 The Networks of Parkinson s Disease 239
10.3 The Thalamus-It s Not a Simple Relay Anymore 240
10.4 The Contribution of China White 241
10.5 Dynamics of Parkinson s Networks 242
10.6 The Deep Brain Stimulation Paradox 246
10.7 Reductionist Cracking the Deep Brain Stimulation Paradox 248
10.8 A Cost Function for Deep Brain Stimulation 256
10.9 Fusing Experimental GPi Recordings with DBS Models 259
10.10 Toward a Control Framework for Parkinson s Disease 259
10.11 Looking Foward 269
11 Control Systems with Electrical Fields 273
11.1 Introduction 273
11.2 A Brief History of the Science of Electrical Fields and Neurons 273
11.3 Applications of Electrical Fields in Vitro 277
11.4 A Brief Affair with Chaos 279
11.5 And a Fling with Ice Ages 283
11.6 Feedback Control with Electrical Fields 284
11.7 Controlling Propagation-Speed Bumps for the Brain 287
11.8 Neurons in the Resistive Brain 289
11.9 How Small an Electrical Field Will Modulate Neuronal
Activity? 290
11.10 Transcranial Low-Frequency Fields 293
11.11 Electrical Fields for Control Within the Intact Brain 293
11.12 To Sleep Perchance to Dream 297
11.13 Toward an Implantable Field Controller 298
12 Assimilating Seizures 301
12.1 Introduction 301
12.2 Hodgkin-Huxley Revisited 302
12.3 The Dynamics of Potassium 306
12.4 Control of Single Cells with Hodgkin-Huxley and
Potassium Dynamics 316
12.5 Assimilating Seizures 319
12.6 Assimilation in the Intact Brain 320
12.7 Perspective 323
13 Assimilating Minds 327
13.1 We Are All State Estimation Machines 327
13.2 Of Mind and Matter 327
Contents
13.3 Robot Beliefs versus Cogito Ergo MRI 328
13.4 Black versus Gray Swans 330
13.5 Mirror, Mirror, within My Mind 332
13.6 Carl Jung s Synchronicity 333
Bibliography 337
Index 357
|
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| spelling | Schiff, Steven J. Verfasser aut Neural control engineering the emerging intersection between control theory and neuroscience Steven J. Schiff Cambridge, MA MIT Press 2012 XVI, 361 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Computational neuroscience series Computational neuroscience Nonlinear control theory Neural Networks (Computer) Brain physiology Models, Neurological Neuroscience Nonlinear Dynamics Robotics Nervennetz (DE-588)4041638-0 gnd rswk-swf Modell (DE-588)4039798-1 gnd rswk-swf Regelungstechnik (DE-588)4076594-5 gnd rswk-swf Kontrolltheorie (DE-588)4032317-1 gnd rswk-swf Neurowissenschaften (DE-588)7555119-6 gnd rswk-swf Nervennetz (DE-588)4041638-0 s Modell (DE-588)4039798-1 s Regelungstechnik (DE-588)4076594-5 s Kontrolltheorie (DE-588)4032317-1 s Neurowissenschaften (DE-588)7555119-6 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024407119&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Schiff, Steven J. Neural control engineering the emerging intersection between control theory and neuroscience Computational neuroscience Nonlinear control theory Neural Networks (Computer) Brain physiology Models, Neurological Neuroscience Nonlinear Dynamics Robotics Nervennetz (DE-588)4041638-0 gnd Modell (DE-588)4039798-1 gnd Regelungstechnik (DE-588)4076594-5 gnd Kontrolltheorie (DE-588)4032317-1 gnd Neurowissenschaften (DE-588)7555119-6 gnd |
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| title | Neural control engineering the emerging intersection between control theory and neuroscience |
| title_auth | Neural control engineering the emerging intersection between control theory and neuroscience |
| title_exact_search | Neural control engineering the emerging intersection between control theory and neuroscience |
| title_full | Neural control engineering the emerging intersection between control theory and neuroscience Steven J. Schiff |
| title_fullStr | Neural control engineering the emerging intersection between control theory and neuroscience Steven J. Schiff |
| title_full_unstemmed | Neural control engineering the emerging intersection between control theory and neuroscience Steven J. Schiff |
| title_short | Neural control engineering |
| title_sort | neural control engineering the emerging intersection between control theory and neuroscience |
| title_sub | the emerging intersection between control theory and neuroscience |
| topic | Computational neuroscience Nonlinear control theory Neural Networks (Computer) Brain physiology Models, Neurological Neuroscience Nonlinear Dynamics Robotics Nervennetz (DE-588)4041638-0 gnd Modell (DE-588)4039798-1 gnd Regelungstechnik (DE-588)4076594-5 gnd Kontrolltheorie (DE-588)4032317-1 gnd Neurowissenschaften (DE-588)7555119-6 gnd |
| topic_facet | Computational neuroscience Nonlinear control theory Neural Networks (Computer) Brain physiology Models, Neurological Neuroscience Nonlinear Dynamics Robotics Nervennetz Modell Regelungstechnik Kontrolltheorie Neurowissenschaften |
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