Neurobiology of Motor Control: Fundamental Concepts and New Directions
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More About This Title Neurobiology of Motor Control: Fundamental Concepts and New Directions

English

A multi-disciplinary look at the current state of knowledge regarding motor control and movement—from molecular biology to robotics

The last two decades have seen a dramatic increase in the number of sophisticated tools and methodologies for exploring motor control and movement. Multi-unit recordings, molecular neurogenetics, computer simulation, and new scientific approaches for studying how muscles and body anatomy transform motor neuron activity into movement have helped revolutionize the field. Neurobiology of Motor Control brings together contributions from an interdisciplinary group of experts to provide a review of the current state of knowledge about the initiation and execution of movement, as well as the latest methods and tools for investigating them.   

The book ranges from the findings of basic scientists studying model organisms such as mollusks and Drosophila, to biomedical researchers investigating vertebrate motor production to neuroengineers working to develop robotic and smart prostheses technologies. Following foundational chapters on current molecular biological techniques, neuronal ensemble recording, and computer simulation, it explores a broad range of related topics, including the evolution of motor systems, directed targeted movements, plasticity and learning, and robotics.  

  • Explores motor control and movement in a wide variety of organisms, from simple invertebrates to human beings
  • Offers concise summaries of motor control systems across a variety of animals and movement types
  • Explores an array of tools and methodologies, including electrophysiological techniques, neurogenic and molecular techniques, large ensemble recordings, and computational methods
  • Considers unresolved questions and how current scientific advances may be used to solve them going forward

Written specifically to encourage interdisciplinary understanding and collaboration, and offering the most wide-ranging, timely, and comprehensive look at the science of motor control and movement currently available, Neurobiology of Motor Control is a must-read for all who study movement production and the neurobiological basis of movement—from molecular biologists to roboticists. 

English

SCOTT L. HOOPER, PhD, is a Professor in the Department of Biological Sciences at Ohio University and Visiting Professor at the University of Cologne.

ANSGAR BÜSCHGES, PhD, is Professor and Head of the Department of Animal Physiology at the University of Cologne. He has served as Dean of the University of Cologne's Faculty of Mathematics and Natural Sciences and is a member of the Executive Committee of the German Neuroscience Society.

English

List of Contributors xiii

About the Cover xvii

1 Introduction 1
Ansgar Büschges and Scott L. Hooper

References 5

2 Electrophysiological Recording Techniques 7
Scott L. Hooper and Joachim Schmidt

2.1 Introduction 7

2.2 Terminology 8

2.3 Intracellular and Patch Clamp Recording 9

2.3.1 Recording Electrodes 9

2.3.2 Current-Clamp:Measuring Transmembrane Potential 12

2.3.3 Voltage Clamp: Measuring Transmembrane Current 15

2.3.3.1 Voltage Clamp with Transmembrane Potential as Reference 15

2.3.3.2 Voltage Clamp with Preparation (Bath) Ground as Reference 16

2.4 Extracellular Recording and Stimulation 17

2.5 A Brief History of Electrophysiological Recording 21

2.6 Concepts Important to Understanding Neuron Recording Techniques 27

2.6.1 Membrane Properties 27

2.6.2 Intracellular Recording 29

2.6.3 Extracellular Recording 32

2.6.3.1 Intracellular Action Potential Shape 33

2.6.3.2 Axon Embedded in Uniform, Infinite Volume Conductor 33

2.6.3.3 Variations in Extracellular Action Potential Shape Induced by Non-Uniform, Non-Infinite Volume Conductors 42

2.6.3.4 Bipolar Recording 44

2.6.3.5 Extracellular Action Potential Summary 46

Acknowledgements 47

References 47

3 Multi-Unit Recording 55
Arthur Leblois and Christophe Pouzat

3.1 Introduction 55

3.2 Chapter Organization and Expository Choices 56

3.3 Hardware 57

3.4 Spike Sorting Methods 60

Endnotes 69

References 70

4 The “New Math” of Neuroscience: Genetic Tools for Accessing and Electively Manipulating Neurons 75
Andreas Schoofs,Michael J. Pankratz, and Martyn Goulding

4.1 Introduction 75

4.2 Restricting Gene Expression to Specific Neurons 76

4.2.1 Promoter Bashing, Enhancer Trapping: Binary Systems for Targeted Gene Expression 77

4.2.2 Intersectional Strategies 81

4.2.3 Temporally Inducible Systems 82

4.3 Tracing, Manipulating, and Monitoring Neurons 84

4.3.1 Tracing Neuronal Projections and Connections with Fluorescent Reporters 84

4.3.2 Viral Tracers for Mapping Neural Connections 85

4.3.3 Manipulating Neuronal Function 87

4.3.4 Monitoring Neuronal Activity 90

4.4 Case Studies 92

4.5 Future Perspective 98

References 98

5 Computer Simulation—Power and Peril 107
Astrid A. Prinz and Scott L. Hooper

5.1 Introduction 107

5.2 Why Model? 107

5.3 Modeling Approaches 110

5.4 Model Optimization and Validation 118

5.5 Beyond Purely ComputationalModels 120

5.6 Fundamental Concepts and Frequently Used Models in Motor Control 121

5.6.1 How to Predict the Future 121

5.6.2 Neuron Models 123

5.6.3 Synapse Models 127

5.6.4 Muscle Models 128

5.6.5 Biomechanical Models 128

5.7 The Future 129

Acknowledgements 130

References 130

6 Evolution of Motor Systems 135
Paul S. Katz and Melina E. Hale

6.1 Introduction 135

6.2 Phylogenetics 136

6.3 Homology and Homoplasy 138

6.4 Levels of Biological Organization 139

6.5 Homologous Neurons 139

6.6 Deep Homology 142

6.7 Homoplasy 145

6.8 Convergence in Central Pattern Generators 150

6.9 Evolutionary Loss 152

6.10 Evolution of Novel Motor Behaviors 152

6.11 Three Scenarios for the Evolution of Novel Behavior 154

6.11.1 Generalist Neural Circuitry 154

6.11.2 Rewired Circuitry 157

6.11.3 Functional Rewiring with Neuromodulation 159

6.12 Motor System Evolvability 161

6.13 Neuron Duplication and Parcellation 162

6.14 Divergence of Neural Circuitry 164

6.15 Summary and Conclusions 165

Acknowledgements 165

References 165

7 Motor Pattern Selection 177

7.1 Introduction to Motor Pattern Selection in Vertebrates and Invertebrates 178
Hans-Joachim Pflüger and Sten Grillner

References 179

7.2 Selection of Action—A Vertebrate Perspective 181

Sten Grillner and Brita Robertson

7.2.1 Introduction 181

7.2.2 Control of Locomotory Outputs 182

7.2.3 The Organization and Role of the Basal Ganglia 184

7.2.4 ConceptualModel of the Organization Underlying Selection of Behavior 187

7.2.5 The Organization of Motor Control From Cortex (Pallium in Lower Vertebrates) 189

7.2.6 The Relative Role of Different Forebrain Structures for Selection of Behavior 189

Acknowledgements 190

References 191

7.3 Motor Pattern Selection and Initiation in Invertebrates with an Emphasis on Insects 195
Hans-Joachim Pflüger

7.3.1 Introduction 195

7.3.2 Organization Principles of Relevant Sensory Systems 196

7.3.3 Movement-Generating Neural Networks in Invertebrates 196

7.3.4 Motor Pattern Selection in Invertebrates 197

7.3.4.1 Probabilistic “Selection”: Intrinsically Variable CPGs in Mollusk Feeding 197

7.3.4.2 Selection via CPG Coordination 198

7.3.4.3 Selection by Neuromodulators or Neurohormones 198

7.3.4.4 Selection by Command Neurons Not in the Brain 201

7.3.4.5 The Brain is Crucial in the Motor Selection Process 202

7.3.5 Two Case Studies 207

7.3.6 Concluding Remarks on Invertebrates 213

7.3.7 Are There Common Themes between Motor Pattern Selection in

Invertebrates and Vertebrates? 213

References 216

8 Neural Networks for the Generation of RhythmicMotor Behaviors 225
Ronald M. Harris-Warrick and Jan-Marino Ramirez

8.1 Introduction 225

8.2 Concept of the Central Pattern Generator 225

8.3 Overall Organization of Rhythmic Motor Networks 227

8.4 Identification of CPG Neurons and Synapses: The “Wiring Diagram” 234

8.5 Cellular PropertiesThat Shape Network Output: Building Blocks for Network Operation 238

8.6 Combined Neural Mechanisms for Rhythmogenesis 240

8.7 Ionic Currents Shaping CPG Network Neuron Intrinsic Firing Properties 241

8.7.1 Role of Outward Currents in Regulating Pacemaker and Network Activity 241

8.7.2 Role of Inward Currents in the Generation of Pacemaker and Network Activity 243

8.7.3 Interaction of Inward and Outward Currents in the Generation of Pacemaker Activity 245

8.7.4 Homeostatic Plasticity and the Balance between Different Ion Channel Types 245

8.7.5 Rapid Changes in Extracellular Ion Concentrations during Rhythmic Network Function 246

8.8 Role of Network Synaptic Properties in Organizing Rhythmic Behaviors 246

8.9 Variable Output from Motor Networks 249

8.10 Conclusions 252

Acknowledgements 253

References 253

9 Sensory Feedback in the Control of Posture and Locomotion 263
Donald H. Edwards and Boris I. Prilutsky

9.1 Introduction 263

9.2 History and Background of Feedback Control 264

9.3 Classical Control Theory 264

9.4 Nervous System Implementation in the Control of Posture and Limb Movements 267

9.5 Organization and Function in Arthropods 274

9.5.1 Locomotory System Gross Anatomy 274

9.5.2 Proprioceptors and Exteroceptors 274

9.5.3 Arthropod Nervous Systems 275

9.5.4 Postures and Movement Commands 275

9.5.5 Sensory Feedback in the Maintenance of Posture 275

9.5.6 Sensory Feedback in Movement andWalking 276

9.6 Organization and Function in Vertebrates 282

9.6.1 Sensory Feedback in the Maintenance of Posture 282

9.6.2 Sensory Feedback and its Integration with Motor Commands in

Movement 285

9.7 Conclusions 293

Acknowledgements 294

Endnote 294

References 294

10 Coordination of Rhythmic Movements 305
Jean-Patrick Le Gal, Réjean Dubuc, and Carmen Smarandache-Wellmann

10.1 Introduction 305

10.2 Overview of Invertebrate CPGs 306

10.2.1 Stomatogastric Nervous System: Feeding Circuits in Decapod Crustacea 308

10.2.2 Leech Locomotion 315

10.2.3 Crayfish Swimmeret System 317

10.2.4 Insect Locomotion 319

10.2.5 MultipleMechanisms Mediate Coordination in Invertebrate Systems 321

10.3 Overview of Vertebrate CPGs 321

10.3.1 General Characteristic of Vertebrate CPGs 322

10.3.1.1 Locomotor CPGs 322

10.3.1.2 Respiratory CPGs 323

10.3.1.3 Feeding CPGs 324

10.3.2 CPG Interactions within One Motor Function 324

10.3.2.1 Unit Generators in Limbless Swimming Vertebrates 324

10.3.2.2 Unit Generators in Mammalian Limbs 325

10.3.3 CPGs Interactions for Different Motor Functions 327

10.3.3.1 Coordination of Respiration and Swallowing 327

10.3.3.2 Coordination of Locomotion and Respiration 328

10.4 Conclusion 331

References 332

11 Prehensile Movements 341
Till Bockemühl

11.1 Introduction: Prehension as Goal-Directed Behavior 341

11.2 The Redundancy Problem in Motor Control 343

11.3 Redundancy Occurs on Multiple Levels of the Motor System 346

11.4 Overcoming the Redundancy Problem 349

11.4.1 InvariantMovement Features 350

11.4.2 Increasing the Number of Task Conditions 352

11.4.3 Reducing the Number of DOFs 357

References 361

12 Muscle, Biomechanics, and Implications for Neural Control 365
Lena H. Ting and Hillel J. Chiel

12.1 Introduction 365

12.2 Behavioral Context Determines How Motorneuron Activity Is Transformed into Muscle Force and Power 366

12.2.1 The Neuromuscular Transform Is History-Dependent 367

12.2.1.1 Motorneurons Are Subject to Neuromodulation and History-Dependence That Can Significantly Alter Their Output 368

12.2.1.2 Presynaptic Neurotransmitter Release at the Neuromuscular Junction Is History-Dependent 368

12.2.1.3 Post-SynapticMuscle Excitation Is History-Dependent and Subject to Modulation 368

12.2.1.4 Contractile Dynamics of Cross-Bridge Interactions Are History Dependent 369

12.2.1.5 The Molecular Motors of Muscles Give Rise to the Functional and History-Dependent Properties of Muscle Force Generation 369

12.2.2 Muscle Power Depends on Behavioral Context 371

12.2.3 Muscle Specialization Reflects Behavioral Repertoire 373

12.3 Organismal Structures Transform Muscle Force into Behavior 374

12.3.1 Effects of Muscle Force Depend on the Properties of the Body and the Environment 375

12.3.1.1 The Relative Importance of Inertial, Viscous, and Spring-Like Forces Affect the Role of Muscle Force 375

12.3.1.2 Muscle Function Depends on Behavioral Context and Environmental Forces 377

12.3.1.3 Biomechanical Affordances and Constraints of Body Structures Affect Muscle Functions 377

12.3.2 Muscles Are Multi-Functional 381

12.3.3 Specialization of Biomechanical Structures Reflect Behavioral Repertoire 385

12.4 Biomechanics Defines Meaningful Patterns of Neural Activity 387

12.4.1 Organismal Structures Are Multi-Functional 389

12.4.2 Many Functionally-Equivalent Solutions Exist for Sensorimotor Tasks 392

12.4.3 Structure and Variability in Motor Patterns Reflect Biomechanics 394

12.4.4 Specialization of Neuromechanical Systems Reflect Behavioral Repertoire 399

12.5 Conclusions 401

Acknowledgements 402

References 402

13 Plasticity and Learning in Motor Control Networks 417
John Simmers and Keith T. Sillar

13.1 Introduction 417

13.2 Homeostatic Motor Network Assembly 418

13.3 Short-Term Motor Learning Conferred by Sodium Pumps 420

13.3.1 Swimming CPG Network Plasticity in Xenopus Frog Tadpoles 420

13.3.2 Comparative Aspects of Na+ Pump Contribution to Neural Network Function 425

13.4 CPG Network Plasticity and Motor Learning Conferred by Operant Conditioning 426

13.5 Discussion and Conclusions 432

References 436

14 Bio-inspired Robot Locomotion 443
Thomas Buschmann and Barry Trimmer

14.1 Introduction 443

14.2 Mechanical Engineering Background and a Biological Example 444

14.3 Legged Robots with Skeletal Structures 446

14.3.1 Mechanism Design, Sensing, and Actuation 446

14.3.2 Basic Dynamics of Legged Locomotion 447

14.3.3 Trajectory-OrientedWalking Control 448

14.3.4 Limit CycleWalkers 450

14.3.5 CPG-Based Control and Step-Phase Control 451

14.4 Soft Robots 452

14.4.1 Limitations and Advantages of Soft Materials 452

14.4.2 The Challenges 453

14.4.2.1 Actuators 453

14.4.2.2 Sensors 455

14.4.2.3 Control of Soft Robots 456

14.4.3 Bioinspired Locomotion in Soft Robots 459

14.5 Conclusion and Outlook 463

References 463

Index 473

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