Computer Science Control Systems Neuromotor control is an interdisciplinary field that investigates how the nervous system processes information to plan, execute, and refine movements. Drawing heavily on principles from control systems, it models the brain and spinal cord as a sophisticated controller that utilizes sensory feedback (e.g., vision, touch) and predictive, feedforward mechanisms to generate precise and adaptive motor commands for muscles. From a computer science perspective, this field employs computational modeling and algorithmic approaches to understand the complex information processing and neural computations that enable everything from simple reflexes to the fluid execution of complex, learned skills like playing a musical instrument.
1.1.
The Motor Control Problem
1.1.1.
Defining Motor Control
1.1.2.
The Degrees of Freedom Problem
1.1.2.1. Concept of Degrees of Freedom
1.1.2.2. Joint Degrees of Freedom
1.1.2.3. Muscle Degrees of Freedom
1.1.2.4. Neural Degrees of Freedom
1.1.3.
Strategies for Reducing Degrees of Freedom
1.1.3.1. Synergies and Coordinative Structures
1.1.3.2. Constraints-Based Approaches
1.1.3.3. Hierarchical Control
1.1.4.
Motor Redundancy
1.1.4.1. Multiple Solutions Problem
1.1.4.2. Functional Redundancy
1.1.4.3. Kinematic Redundancy
1.1.4.4. Dynamic Redundancy
1.1.5.
Motor Equivalence
1.1.5.1. Definition and Principles
1.1.5.2. Examples in Human Movement
1.1.5.3. Flexibility in Motor Solutions
1.1.6.
Context-Conditioned Variability
1.1.6.1. Environmental Constraints
1.1.6.3. Organismic Constraints
1.1.6.4. Interaction of Constraints
1.2.
Key Terminology and Concepts
1.2.1.
Motor Action versus Movement
1.2.1.1. Definitions and Distinctions
1.2.1.2. Goal-Directed Actions
1.2.1.3. Kinematic Descriptions
1.2.2.
Motor Skills
1.2.2.1. Definition of Motor Skill
1.2.2.3. Continuous Skills
1.2.2.7. Fine Motor Skills
1.2.2.8. Gross Motor Skills
1.2.3.
Motor Programs
1.2.3.1. Concept of Motor Programs
1.2.3.2. Generalized Motor Programs
1.2.3.3. Motor Schema Theory
1.2.3.4. Hierarchical Organization
1.2.4.
Motor Control versus Motor Learning
1.2.4.1. Definitional Distinctions
1.2.4.3. Performance versus Learning
1.3.
Anatomical and Physiological Foundations
1.3.1.
The Neuron
1.3.1.1. Neuronal Structure
1.3.1.1.4. Synaptic Terminals
1.3.1.2.1. Sensory Neurons
1.3.1.3.1. Resting Potential
1.3.2.
Synaptic Transmission
1.3.2.1. Chemical Synapses
1.3.2.1.1. Neurotransmitter Release
1.3.2.1.2. Receptor Binding
1.3.2.1.3. Postsynaptic Potentials
1.3.2.2. Electrical Synapses
1.3.2.2.2. Synchronization
1.3.2.3. Neurotransmitters in Motor Control
1.3.3.
Muscle Physiology
1.3.3.1. Skeletal Muscle Structure
1.3.3.1.1. Muscle Fiber Organization
1.3.3.2. Muscle Fiber Types
1.3.3.2.2. Type IIa Fibers
1.3.3.2.3. Type IIx Fibers
1.3.3.2.4. Functional Characteristics
1.3.3.3. Sliding Filament Theory
1.3.3.3.1. Actin and Myosin
1.3.3.3.2. Cross-Bridge Cycling
1.3.3.3.3. ATP Requirements
1.3.3.4. Excitation-Contraction Coupling
1.3.3.4.1. Neuromuscular Junction
1.3.3.4.2. Calcium Release
1.3.3.4.3. Troponin-Tropomyosin Complex
1.3.4.
The Motor Unit
1.3.4.1. Definition and Components
1.3.4.2.1. Slow Motor Units
1.3.4.2.2. Fast Fatigue-Resistant Motor Units
1.3.4.2.3. Fast Fatigable Motor Units
1.3.4.3. Motor Unit Recruitment
1.3.4.3.1. Henneman's Size Principle
1.3.4.3.2. Recruitment Order
1.3.4.4.1. Spatial Summation
1.3.4.4.2. Temporal Summation