The computational neurobiology of reaching and pointing: a foundation for motor learning
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge, Mass. [u.a.]
MIT Press
2005
|
| Schriftenreihe: | Computational neuroscience
A Bradford book |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013176845&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XVIII, 575 S. Ill., graph. Darst. |
| ISBN: | 0262195089 |
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| 245 | 1 | 0 | |a The computational neurobiology of reaching and pointing |b a foundation for motor learning |c Reza Shadmehr and Steven P. Wise |
| 264 | 1 | |a Cambridge, Mass. [u.a.] |b MIT Press |c 2005 | |
| 300 | |a XVIII, 575 S. |b Ill., graph. Darst. | ||
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| 490 | 0 | |a Computational neuroscience | |
| 490 | 0 | |a A Bradford book | |
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| 650 | 7 | |a Motorische ontwikkeling |2 gtt | |
| 650 | 7 | |a Neurobiologie |2 gtt | |
| 650 | 7 | |a Visuomotorische coördinatie |2 gtt | |
| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Motor ability | |
| 650 | 4 | |a Motor learning | |
| 650 | 4 | |a Motor learning |x Mathematical models | |
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Datensatz im Suchindex
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| adam_text | Contents in Brief
Contents in Detail ix
Preface xv
1 Introduction 1
I Evolution, Anatomy, and Physiology 7
2 Our Moving History: The Evolution of the Vertebrate CNS 9
3 Burdens of History: Control Problems That Reach from the Past
27
4 What Motor Learning Is, What Motor Learning Does 39
5 What Does the Motor Learning I: Spinal Cord and Brainstem
61
6 What Does the Motor Learning II: Forebrain 75
7 What Generates Force and Feedback 93
8 What Maintains Limb Stability 119
II Computing Locations and Displacements 141
9 Computing End Effector Location I: Theory 143
10 Computing End Effector Location II: Experiment 159
11 Computing Target Location 179
12 Computing Difference Vectors I: Fixation Centered Coordinates
205
13 Computing Difference Vectors II: Parietal and Frontal Cortex
229
14 Planning Displacements and Forces 245
viii Contents in Brief
III Skills, Adaptation, and Trajectories 271
15 Aligning Vision and Proprioception I: Adaptation and Context
273
16 Aligning Vision and Proprioception II: Mechanisms and
Generalization 295
17 Remapping, Predictive Updating, and Autopilot Control 319
18 Planning to Reach or Point I: Smoothness in Visual
Coordinates 341
19 Planning to Reach or Point II: A Next State Planner 353
IV Predictions, Decisions, and Flexibility 377
20 Predicting Force I: Internal Models of Dynamics 379
21 Predicting Force II: Representation and Generalization 403
22 Predicting Force III: Consolidating a Motor Skill 435
23 Predicting Inputs and Correcting Errors I: Filtering and
Teaching 447
24 Predicting Inputs and Correcting Errors II: Learning from
Reflexes 473
25 Deciding Flexibly on Goals, Actions, and Sequences 495
V Glossary and Appendixes 525
Glossary 527
Appendix A. Biology Refresher 533
Appendix B. Anatomy Refresher 537
Appendix C. Mathematics Refresher 539
Appendix D. Physics Refresher 543
Appendix E. Neurophysiology Refresher 547
Index 549
Contents in Detail
Preface xv
1 Introduction 1
1.1 Why Motor Learning? 1
1.2 Why Now? 2
1.3 Why a Theoretical Study? 3
1.4 Why a Computational Theory? 3
1.5 Why Vertebrates, Why Primates, and Why a Two Joint Arm? 4
I Evolution, Anatomy, and Physiology 7
2 Our Moving History: The Evolution of the Vertebrate CNS 9
2.1 Birth of the Motor System 9
2.2 Components of the Motor System 10
2.3 A Brief History of the Motor System 12
2.4 First Steps: Inventing the Vertebrate Brain 15
2.5 More Recent Steps: Cerebellum and Motor Cortex 21
2.6 Summary 23
3 Burdens of History: Control Problems That Reach from the Past
27
3.1 Limbs 28
3.2 Muscles 32
3.3 Nerves 37
4 What Motor Learning Is, What Motor Learning Does 39
4.1 Motor Learning Undefined 39
4.2 Motor Learning over Generations: Links to Instincts and Reflexes
41
4.3 Learning New Skills and Maintaining Performance 46
4.4 Making Decisions Adaptively 51
4.5 Summary 58
5 What Does the Motor Learning I: Spinal Cord and Brainstem
61
5.1 Spinal Cord 61
x Contents in Detail
5.2 Hindbrain 65
5.3 Cerebellum 68
5.4 Red Nucleus 71
5.5 Superior Colliculus 73
6 What Does the Motor Learning II: Forebrain 75
6.1 Basal Ganglia 75
6.2 Thalamus 80
6.3 Cortical Organization I: General Considerations 81
6.4 Cortical Organization II: Cortical Fields for Reaching and Pointing
85
7 What Generates Force and Feedback 93
7.1 Biological Versus Mechanical Actuators 93
7.2 Muscle Mechanisms 94
7.3 Motor Units 98
7.4 A Muscle Model 99
7.5 Converting Force to Torque 102
7.6 Muscle Afferents 108
7.7 Muscle Afferents in Action 112
8 What Maintains Limb Stability 119
8.1 Equilibrium Points from Antagonist Muscle Activity 120
8.2 Restoring Torques from Length Tension Properties 121
8.3 Stiffness from Muscle Coactivation 123
8.4 Reaching Without Feedback in Monkeys 123
8.5 Equilibrium Points from Artificial Stimulation 126
8.6 Rapid Movements from Sequential Muscle Activation 127
8.7 Passive Properties Produce Stability 129
8.8 Reflexes Produce Stability 131
8.9 Reaching Without Feedback in Humans 135
8.10 Passive Properties and Reflexes Combined 136
II Computing Locations and Displacements 141
9 Computing End Effector Location I: Theory 143
9.1 Reaching and Pointing Require Sensory Feedback 143
9.2 Kinematics and Dynamics 144
9.3 Degrees of Freedom and Coordinate Frames 144
9.4 End Effectors and Adaptive Mapping 146
9.5 Predicting the Location of an End Effector in Visual Coordinates 147
9.6 Predicting End Effector Location with Proprioception: Virtual Robotics
148
9.7 Predicting End Effector Location with Proprioception: Computations
151
10 Computing End Effector Location II: Experiment 159
10.1 Role of Proprioceptive Signals in End Effector Localization 159
10.2 Introduction to Frontal and Parietal Neurophysiology 162
xi Contents in Detail
10.3 Encoding of Limb Configuration in the CNS 165
10.4 Errors in Reaching due to Lesions of the PPC 175
11 Computing Target Location 179
11.1 Computing Target and End Effector Locations in a Common Frame
180
11.2 Computing Target Location in a Vision Based Frame 183
11.3 Combining Retinal Location with Eye Orientation Through Gain
Fields 188
12 Computing Difference Vectors I: Fixation Centered Coordinates
205
12.1 Planning Reaching and Pointing with Difference Vectors 205
12.2 Shoulder Centered Versus Fixation Centered Coordinates 209
12.3 Planning in Fixation Centered Coordinates: Experiment 212
12.4 Planning in Fixation Centered Coordinates: Theory 216
12.5 Localizing an End Effector in Fixation Centered Coordinates 221
12.6 Encoding End Effector Location in Fixation Centered Coordinates
222
12.7 Issues Concerning Fixation Centered Coordinates 225
13 Computing Difference Vectors II: Parietal and Frontal Cortex
229
13.1 Computing a Movement Plan 229
13.2 Planning Potential Movements but Not Executing Them 237
13.3 Planning the Next Movement in a Sequence 241
14 Planning Displacements and Forces 245
14.1 Representing the Difference Vector in the Motor Areas of the Frontal
Lobe 247
14.2 Population Vectors, Force Coding, and Coordinate Frames in Ml
261
III Skills, Adaptation, and Trajectories 271
15 Aligning Vision and Proprioception I: Adaptation and Context
273
15.1 Newts Cannot Adapt to Rotation of Their Eyes 275
15.2 Primates Adapt to Rotation of the Visual Field 276
15.3 Prism Adaptation Requires Modification of Both Location and
Displacement Maps 279
15.4 Long term Memories and Learning to Switch on Context 280
15.5 Prism Adaptation in Virtual Robotics 284
15.6 Consequences of Planning in Vision Based Coordinates 286
15.7 Moving an End Effector Attached to the Hand 288
15.8 Internal Models of Kinematics 289
15.9 Estimate of Limb Location Is Influenced by the Likelihood of the
Sensed Variables 291
xii Contents in Detail
16 Aligning Vision and Proprioception II: Mechanisms and
Generalization 295
16.1 Neural Systems Involved in Adapting Alignments Between
Proprioception and Vision 295
16.2 Generalization of Adaptation to Altered Visual Feedback 303
17 Remapping, Predictive Updating, and Autopilot Control 319
17.1 Remapping Target Location 319
17.2 Predictive Remapping of Target and End Effector Location with
Efference Copy 325
17.3 Remapping End Effector Location 331
18 Planning to Reach or Point I: Smoothness in Visual Coordinates
341
18.1 Regularity in Reaching and Pointing 343
18.2 Description of Trajectory Smoothness: Minimum Jerk 350
19 Planning to Reach or Point II: A Next State Planner 353
19.1 The Problem of Planning 353
19.2 Transforming a Displacement Vector into a Trajectory 354
19.3 The Next State Planner 357
19.4 Minimizing the Effects of Signal Dependent Noise 364
19.5 Online Correction of Self Generated and Imposed Errors in
Huntington s Disease 366
19.6 Transforming Plans into Trajectories: The Problem of Redundancy
371
IV Predictions, Decisions, and Flexibility 377
20 Predicting Force I: Internal Models of Dynamics 379
20.1 Internal Models of Dynamics 380
20.2 Correlates of Adapting to Altered Dynamics 391
21 Predicting Force II: Representation and Generalization 403
21.1 The Coordinate System of the Internal Model of Dynamics 403
21.2 Computing an Internal Model with a Population Code 410
21.3 Estimating Generalization Functions from Trial to Trial Changes in
Movement 416
21.4 A Not So Invariant Desired Trajectory 432
22 Predicting Force III: Consolidating a Motor Skill 435
22.1 Consolidation 435
22.2 A Role for Time and Sleep in Consolidation of Motor Memories
441
23 Predicting Inputs and Correcting Errors I: Filtering and Teaching
447
23.1 Cancellation of Predicted Signals by Adaptive Filtering 449
23.2 Predicting and Responding to a Stimulus 454
23.3 Similar Learning Mechanisms in Basal Ganglia and Cerebellum
462
xiii Contents in Detail
23.4 A Training Signal for the Basal Ganglia 464
23.5 Why Does Huntington s Disease Result in Disorders in Reaching?
468
24 Predicting Inputs and Correcting Errors II: Learning from
Reflexes 473
24.1 Climbing Fibers Encode a Signal That Represents Motor Error 475
24.2 Predictively Correcting Motor Commands 480
25 Deciding Flexibly on Goals, Actions, and Sequences 495
25.1 Deciding on a Target 496
25.2 Choosing Among Multiple Potential Targets of Movement 503
25.3 Deciding on Multiple Movements 504
25.4 Action Selection Based on Estimates of State 505
25.5 Moving to Places Other Than a Stimulus: Standard Mapping vs.
Nonstandard Mapping 513
25.6 Summary 519
V Glossary and Appendixes 525
Glossary 527
Appendix A Biology Refresher 533
Appendix B Anatomy Refresher 537
Appendix C Mathematics Refresher 539
Appendix D Physics Refresher 543
Appendix E Neurophysiology Refresher 547
Index 549
|
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| dewey-ones | 152 - Perception, movement, emotions & drives |
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| discipline | Physik Biologie Informatik Psychologie |
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| id | DE-604.BV019852170 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T12:07:16Z |
| institution | BVB |
| isbn | 0262195089 |
| language | English |
| lccn | 2004042610 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-013176845 |
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| physical | XVIII, 575 S. Ill., graph. Darst. |
| publishDate | 2005 |
| publishDateSearch | 2005 |
| publishDateSort | 2005 |
| publisher | MIT Press |
| record_format | marc |
| series2 | Computational neuroscience A Bradford book |
| spellingShingle | Shadmehr, Reza Wise, Steven P. The computational neurobiology of reaching and pointing a foundation for motor learning Computermodellen gtt Motorische ontwikkeling gtt Neurobiologie gtt Visuomotorische coördinatie gtt Mathematisches Modell Motor ability Motor learning Motor learning Mathematical models Neurobiologie (DE-588)4041871-6 gnd Motorisches Lernen (DE-588)4170603-1 gnd Computersimulation (DE-588)4148259-1 gnd |
| subject_GND | (DE-588)4041871-6 (DE-588)4170603-1 (DE-588)4148259-1 |
| title | The computational neurobiology of reaching and pointing a foundation for motor learning |
| title_auth | The computational neurobiology of reaching and pointing a foundation for motor learning |
| title_exact_search | The computational neurobiology of reaching and pointing a foundation for motor learning |
| title_full | The computational neurobiology of reaching and pointing a foundation for motor learning Reza Shadmehr and Steven P. Wise |
| title_fullStr | The computational neurobiology of reaching and pointing a foundation for motor learning Reza Shadmehr and Steven P. Wise |
| title_full_unstemmed | The computational neurobiology of reaching and pointing a foundation for motor learning Reza Shadmehr and Steven P. Wise |
| title_short | The computational neurobiology of reaching and pointing |
| title_sort | the computational neurobiology of reaching and pointing a foundation for motor learning |
| title_sub | a foundation for motor learning |
| topic | Computermodellen gtt Motorische ontwikkeling gtt Neurobiologie gtt Visuomotorische coördinatie gtt Mathematisches Modell Motor ability Motor learning Motor learning Mathematical models Neurobiologie (DE-588)4041871-6 gnd Motorisches Lernen (DE-588)4170603-1 gnd Computersimulation (DE-588)4148259-1 gnd |
| topic_facet | Computermodellen Motorische ontwikkeling Neurobiologie Visuomotorische coördinatie Mathematisches Modell Motor ability Motor learning Motor learning Mathematical models Motorisches Lernen Computersimulation |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013176845&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT shadmehrreza thecomputationalneurobiologyofreachingandpointingafoundationformotorlearning AT wisestevenp thecomputationalneurobiologyofreachingandpointingafoundationformotorlearning |
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Teilbibliothek Sport- und Gesundheitswissenschaften
| Signatur: |
2502 PHY 825 2017 B 1712 Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |
| Exemplar 2 | Ausleihbar Am Standort |