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Computer Science
Control Systems
Neuromotor Control
1. Foundations of Neuromotor Control
2. Neural Substrates of Motor Control
3. Control System Principles
4. Sensory Systems for Motor Control
5. Motor Learning and Plasticity
6. Control of Specific Motor Behaviors
7. Computational Approaches
8. Motor Control Disorders
Control System Principles
Open-Loop Control
Characteristics
No Feedback
Preprogrammed Commands
Fast Execution
Applications
Ballistic Movements
Rapid Movements
Saccadic Eye Movements
Anticipatory Postural Adjustments
Feedforward Control
Postural Preparation
Limitations
No Error Correction
Environmental Uncertainty
Closed-Loop Control
Characteristics
Feedback-Based
Error Correction
Slower Response
Feedback Types
Proprioceptive Feedback
Visual Feedback
Vestibular Feedback
Tactile Feedback
Control Loops
Negative Feedback
Positive Feedback
Stability Issues
Time Delays
Sensory Delays
Processing Delays
Motor Delays
Applications
Precise Movements
Slow Movements
Postural Control
Hybrid Control Systems
Combination Strategies
Switching Between Modes
Optimal Control Selection
Internal Models
Forward Models
Sensory Prediction
Efference Copy
State Estimation
Motor Imagery
Inverse Models
Motor Command Generation
Desired Outcome Achievement
Model Learning
Error-Based Learning
Adaptation Mechanisms
MOSAIC Architecture
Multiple Paired Models
Context-Dependent Selection
Modular Organization
Optimal Control Theory
Cost Functions
Minimum Jerk
Minimum Energy
Minimum Variance
Minimum Time
Constraints
Kinematic Constraints
Dynamic Constraints
Neural Constraints
Stochastic Optimal Control
Signal-Dependent Noise
Uncertainty Handling
Bayesian Approaches
Prior Knowledge
Likelihood Functions
Posterior Estimation
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2. Neural Substrates of Motor Control
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4. Sensory Systems for Motor Control