
Neural Dynamics of Adaptive Sensory-Motor Control
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Content
- Front Cover
- Neural Dynamics of Adaptive Sensory-Motor Control: Ballistic Eye Movements
- Copyright Page
- Table of Contents
- CHAPTER 1. MULTIPLE LEARNING PROBLEMS ARE SOLVED BY SENSORY-MOTOR SYSTEMS
- 1.1. Introduction: Brain Designs are Adaptive Designs
- 1.2. Eye Movements as a Model Sensory-Motor System
- 1.3. Intermodality Circular Reactions: Learning Gated by Comparison of Target, Position with Present Position
- 1.4. Learning a Target Position Map
- 1.5. From Multimodal Target Map to Unimodal Motor Map
- 1.6. Vector Maps from Comparisons of Target Position Maps and Present Position Maps
- 1.7. Automatic Compensation for Present Position: Code Compression
- 1.8. Outflow vs. Inflow in the Registration of Present Position
- 1.9. Corollary Discharges and Calibration of Muscle Plant Contractions
- 1.10. Outflow-Inflow Pattern Matches and Linearization of Muscle Responses: Automatic Gain Control
- 1.11. Motor Vectors Calibrated by visual Error Signals
- 1.12. Postural Stability: Separate Calibration of Muscle Length and Tension
- 1.13. Planned vs. Reactive Movements: The Rear View Mirror Problem
- 1.14. Attentional Gating
- 1.15. Intermodality Interactions in a Head Coordinate Frame
- 1.16. Head Coordinate Maps Encode Predictive Saccades
- 1.17. The Relationship between Macrotheory and Microtheory
- CHAPTER 2. PARALLEL PROCESSING OF MOVEMENT AND ERROR SIGNALS
- 2.1. Sensory-Motor Coordinates: Hemifield Gradients
- 2.2. Choice of Fixation Light: Network Competition
- 2.3. Correcting Fixation Errors: Competition Precedes Storage in Sensory Short Term Memory
- 2.4. Parallel Processing of Movement and Error Signals
- 2.5. Why Does A Saccade Generator Exist?
- 2.6. Competitive Choice and Storage in Short Term Memory
- CHAPTER 3. SACCADIC LEARNING USING VISUAL ERROR SIGNALS: SELF-MOTION VS. WORLD-MOTION AND CEREBELLAR DYNAMICS
- 3.1. Compensation for Initial Position in the Movement Signal
- 3.2. Explicit vs. Implicit Knowledge of Initial Position
- 3.3. Characterization of Correctable Errors
- 3.4. Self-Movement vs. World-Movement: Ballistic vs. Continuous Movement
- 3.5. A Universal Adaptive Gain Control Mechanism: Saccades, VOR, Posture, and Muscle Gain
- 3.6. Compatibility of Design Hypotheses
- 3.7. Different Coordinates for Unconditioned and Conditioned Movement Systems
- 3.8. Correcting Undershoot, Overshoot, and Skewed Saccadic Errors
- 3.9. Curvature Distorting Contact Lens vs. Inverting Contact Lens
- 3.10. Equal Access to Error Signals: Separate Anatomies for Unconditioned Movements and Conditioned Gain Changes
- 3.11. Anatomical Interpretation of the Adaptive Gain Stage: The Cerebellum
- 3.12. Superposition of Sampling Map and Error Signal Map: Logarithms and Bidirectional Parallel Fibers
- 3.13. Fractured Somatotopy and/or Bilateral Cerebellar Organization
- 3.14. More Constraints on Cerebellar Learning
- 3.15. Dual Action, Incremental Learning, and Error Signal Attenuation
- 3.16. Numerical Studies of Adaptive Foveation due to Cerebellar Gain Changes: Learned Compensation for System Nonlinearities
- 3.17. Shared Processing Load and Recovery from Lesions
- 3.18. Models of Saccadic Error Correction
- 3.19. Dynamic Coasting
- 3.20. Outflow-Inflow Comparisons: A Large Movement as a Series of Small Movement Segments
- 3.21. Mismatch due to Plant Nonlinearity or to Dynamic Coasting?
- 3.22. Adaptive Control of Dynamic Coasting
- CHAPTER 4. COMPARING TARGET POSITION WITH PRESENT POSITION: NEURAL VECTORS
- 4.1. Reconciling Visually Reactive and Intentional Computations
- 4.2. Experimental Evidence for Vector Inputs to the Superior Colliculus
- 4.3. Adaptive Inhibitory Efference Copy in Motor Control
- 4.4. Multistage Elaboration of a Vector Map
- 4.5. Attention Modulation in Parietal Cortex and Inhibitory Gating of SC Signals: The Delay in Vector Subtraction
- 4.6. Stages in the Adaptive Neural Computation of a Vector Difference
- 4.7. Modulators of Head-to-Muscle Coordinate Learning
- 4.8. Mathematical Design of the Head-Muscle Interface
- 4.9. Muscle Linearization and Retinotopic Recoding
- 4.10. Saccade Staircases and Automatic Compensation for Present Position
- 4.11. Corrective Saccades in the Dark: An Outflow Interpretation
- CHAPTER 5. ADAPTIVE LINEARIZATION OF THE MUSCLE PLANT
- 5.1. Fast Corrective Saccades vs. Slow Muscle Linearization
- 5.2. Muscle Linearization Network
- 5.3. Cerebellar Direct Response Cells
- 5.4. Adaptation To Strabismus Surgery
- 5.5. Error Correction with and without Adaptive Gain Changes
- 5.6. Matching within the Outflow-Inflow Interface
- 5.7. An Explanation of the Steinbach and Smith Data
- 5.8. A Role for Golgi Tendon Organs in Muscle Linearization
- 5.9. Dynamic Linearization: Adaptive Sampling during Saccades
- 5.10. An Agonist-Antagonist Ratio Scale
- 5.11. Sampling from a Spatial Map of Outflow Position
- CHAPTER 6. SPATIAL MAPS OF MOTOR PATTERNS
- 6.1. The General Problem: Transforming Pattern Intensities into Map Positions
- 6.2. Antagonistic Positional Gradients, Contrast Enhancement, and Coincidence Detectors
- 6.3. Position-Threshold-Slope Shift, Maps
- 6.4. Self-organizing Spatial Maps
- 6.5. Activity-Dependent Map Formation
- 6.6. Coding of Movement Length and Direction
- 6.7. Normalization of Total PTS Shift Map
- CHAPTER 7. SACCADE GENERATOR AND SACCADE RESET
- 7.1. Saccade Generator
- 7.2. Converting an Intensity Code into a Duration Code
- 7.3. Summation of Retinotopic and Initial Eye Position Signals Signals to the Saccade Generator
- 7.4. The Eye Position Update Network
- 7.5. Two Types of Initial Position Compensation: Eye Position Update and Muscle Linearization
- 7.6. Saccade Staircases
- 7.7. Circuit Design of the Eye Position Update Network
- 7.8. A Saccade Generator Circuit
- 7.9. Computer Simulations of a Saccade Generator Model
- 7.10. Comparison of Computer Simulations with Neural Data
- CHAPTER 8. POSTURAL STABILITY AND LENGTH- TENSION REGULATION
- 8.1. Separate Postural and Movement Systems
- 8.2. Tension Equalization Network
- 8.3. Design of the Tension Equalization Network
- 8.4. Adaptive Step Gain and Pulse Gain: Correcting Post-Saccadic Drift
- 8.5. Relationship to the Vestibulo-Ocular Reflex
- 8.6. Cerebellar Functional Heterogeneity
- CHAPTER 9. SACCADIC RHYTHM AND PREDICTIVE MOVEMENT SEQUENCES
- 9.1. Rhythmic Choices among Multiple Movement Sources
- 9.2. Distinguishing Correct Predictive Saccades from Incorrect Individual Saccades
- 9.3. The Temporal Control of Predictive Saccades
- 9.4. Storage of Temporal Order Information
- 9.5. Design of a Predictive Command Network
- 9.6. Saccade Generation by Predictive Commands
- 9.7. Two Types of Output Gates: Target-Driven Gates and Saccade-Driven Gates
- 9.8. Parietal Light-Sensitive and Saccade Neurons
- 9.9. Switching between Movement and Postural Eye Position Maps: Frontal Eye Field Control
- 9.10. Direct Computation of Predictive Difference Vectors from Stored Retinotopic Positions?
- CHAPTER 10. FORMATION OF AN INVARIANT TARGET POSITION MAP
- 10.1. Invariant Self-Regulating Multimodal Maps
- 10.2. Prewired Positional Gradients: The Mean Value Property
- 10.3. Self-organizing Target Position Maps: Multimodal Sampling of a Unimodal Eye Position Map
- 10.4. Double Duty by Sampling Maps and their Neural Interpretation
- 10.5. Associative Learning at Autoreceptive Synaptic Knobs
- 10.6. Multimodal Learning of Invariant Self-Regulating Spatial Maps
- 10.7. Multimodal Learning of an Invariant Self-Regulating Target Position Map
- 10.8. Associative Pattern Learning
- CHAPTER 11. VISUALLY REACTIVE, MULTIMODAL, INTENTIONAL, AND PREDICTIVE MOVEMENTS: A SYNTHESIS
- 11.1. Avoiding Infinite Regress: Planned Movements Share Reactive Movement Parameters
- 11.2. Learning and Competition from a Vector-Based Map to a Light-Based Map
- 11.3. Associative Pattern Learning and Competitive Choice: Non-Hebbian Learning Rule
- 11.4. Light Intensity, Motion, Attentional, and Multimodal Interactions within the Parietal Cortex
- 11.5. Nonspecific and Specific Attentional Mechanisms
- 11.6. Multiple Retinotopic Maps
- 11.7. Interactions between Superior Colliculus, Visual Cortex and Parietal Cortex
- 11.8. Multiple Target Position Maps within Parietal Cortex and Frontal Eye Fields
- 11.9. Learning Multiply-Activated Target Position Maps
- 11.10. Multiple Parietal and Frontal Eye Field Vector Systems
- 11.11. Learning Neural Vectors and Adaptive Gains in a Predictive Movement System
- 11.12. Frontal Eye Field Control of Voluntary Saccadic Eye Movements and Posture: Cell Types
- 11.13. Coupled Vector and Adaptive Gain Learning
- 11.14. Gating of Learning, Movement, and Posture
- 11.15. When Saccade Choice May Fail: Saccadic Averaging and Partial Vector Compensation
- CHAPTER 12. ARE THERE UNIVERSAL PRINCIPLES OF SENSORY-MOTOR CONTROL?
- REFERENCES
- AUTHOR INDEX
- SUBJECT INDEX
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