Slide-by-slide detailed notes

EXSS3062 Motor Control (MC 10) – “Controlling Motor Output: Motor-Unit Recruitment & Muscle Force”

Slide 1 – Title & context

• Unit & lecture identifier: EXSS3062 Motor Control & Learning – MC 10.

• Topic focus: Motor-unit (MU) recruitment and muscle-force regulation.

• Lecturer: Prof. Stephen Cobley, Faculty of Medicine & Health.

• Signals that the session bridges neural control (motor output) with applied muscle mechanics.

Slide 2 – Acknowledgement of Country

• Recognises the Traditional Custodians of lands on which the University of Sydney stands.

• Emphasises respect for ongoing cultural stewardship; artwork credit given to Luke Penrith’s Yanhambabirra Burambabirra Yalbailinya (2020).

Slide 3 – Copyright notice

• Material reproduced under Part VB of the Copyright Act 1968.

• Reminder: no unauthorised further copying or communication.

Slide 4 – Movement information flow chart

• Afferent (sensory) vs efferent (motor) streams feeding the CNS.

• Lists key sensory sources (muscle spindles, GTOs, cutaneous, vestibular, vision, sound) → inform perception, cognition & planning.

• Efference copy concept introduced—internal prediction of movement consequences.

• Outcome: graded neural commands to overcome biomechanical constraints and drive muscular contraction.

Slide 5 – Learning outcomes

1. Describe three hierarchical output-control “levels” that create versatile movement through MU recruitment.

2. Relate task-specific force & energetic demands to recruitment strategy.

3. Explain Henneman’s size principle (1965).

4. Show why precision drops from low to maximal force outputs.

Slide 6 – Recommended reading

• Magill & Anderson Motor Learning & Control (11th & 12th eds) – Ch. 4 Neurological Basis of Motor Control.

• Sets theoretical background for neural organisation of movement.

Slide 7 – Introduction & Sherrington quote

• Sherrington (1924): “To move things is all that mankind can do… the sole executant is muscle.”

• Frames muscle contraction as the final common pathway of CNS processing.

• Stresses requirement for a continuum of skills: high-precision low-force (e.g., flute embouchure) ↔ max-force ballistic actions.

Slide 8 – Skill spectrum illustration (precision ↔ ballistic)

• Graphical time-series traces show fine EMG modulation in flute vs large bursts in drumming.

• Establishes versatility as the core control challenge.

Slide 9 – CNS neural signalling: versatility demands

• CNS must scale magnitude, frequency & timing of MU activity to task demands.

• Muscles may act independently or in synergies.

• Stable yet rapidly adjustable force output underlies skilled movement.

Slide 10 – Energetic cost constraint

• Force generation capped by fatigue limits.

• “Trying harder” is inefficient; skill learning involves reducing energetic cost or increasing work per unit ATP under time-pressure tasks.

Slide 11 – Level 1 Output Control: CNS planning & signalling

• MU = α-motor neuron + its muscle fibres; neural control acts at MU, not single fibres.

• Typical muscles: ~100 MUs organising thousands of fibres in parallel.

• CNS “plans” desired force profile, then patterns MU activation accordingly.

Slide 12 – Level 2 Output Control: MU number & size

• Diagram contrasting large vs small MUs: larger units innervate wider cross-section → higher force potential.

• Recruitment order (detailed later) progressively taps larger units to scale force.

Slide 13 – Large vs small MU visual example

• Large MU recruits more fibres → greater CSA stimulated.

• Highlights spatial mapping: MU territories overlap, permitting smooth force gradation.

Slide 14 – Motor-unit recruitment video cue

• YouTube link (Dtwow0BXW5c) demonstrates sequential MU activation as contraction force rises.

• Reinforces Level 2 concept through dynamic imagery.

Slide 15 – Level 3 Output Control: MU muscle-composition

• Three fibre phenotypes within mammalian muscle:
  

  • Type I (SO): slow, fatigue-resistant, oxidative.

  • Type IIa (FOG): fast, moderately fatigue-resistant, mixed metabolism.

  • Type IIb (FG): fastest, fatiguable, anaerobic.

Slide 16 – Type I & IIa characteristics

• Type I: sustained contractions via continuous ATP resynthesis (glucose + O₂).

• Type IIa: blends speed with enough aerobic capacity for minutes of activity—ideal for middle-distance efforts.

Slide 17 – Type IIb characteristics & limitation

• Relies on glycogen-driven anaerobic glycolysis; rapid ATP but high lactate.

• Effective for brief bursts; hours required for glycogen restoration post-max bursts.

Slide 18 – Fibre-type comparison table (Kandel et al.)

• Visual juxtaposition of contraction speed, force, fatigue rate, energy economy across Type I → IIa → IIb.

• Demonstrates output versatility achieved by mixing MU types.

Slide 19 – Henneman’s Size Principle (1965)

• Recruit small, fatigue-resistant MUs first, progressing to large, fast units as force demand rises.

• Ensures energy conservation & graded force increments.

Slide 20 – Force vs %MU activated graph

• Slow-twitch units contribute ≤1 % of peak force; fast-fatigable units responsible for explosive peaks.

• Non-linear curve: small MU additions produce larger absolute force jumps at high activation levels.

Slide 21 – Energetic cost of contraction

• Both force and ATP cost rise non-linearly with recruitment.

• High-level activation is disproportionately expensive → training seeks economy at required force range.

Slide 22 – Functional purposes of size principle

1. Fatigue minimisation: preserve fast units until essential.

2. Proportional control: number/type of active MUs + firing rate determines force; precision declines with larger jumps.

Slide 23 – Precision-force trade-off concept

• As more/larger MUs are added, neural “noise” (output variability) rises → degraded fine control.

Slide 24 – O’Dwyer & Neilson (2000) experiment

• Tracking task using elbow flexor; higher-force pulses show jagged profiles & ↑SD of peak force.

• Empirical evidence of loss of accuracy with increased force.

Slide 25 – Practical implication: variability in maximal tasks

• E.g., vertical-jump take-offs exhibit larger inter-trial force fluctuations vs sub-max jumps—skills training aims to stabilise high-force outputs.

Slide 26 – Accuracy vs force summary

• Skilled performers exploit low-force regimes when precision paramount; accept reduced accuracy where high force unavoidable.

Slide 27 – Dual challenge for learning

• Improve energy economy and movement accuracy through re-organisation of efferent signalling and MU recruitment strategies.

Slide 28 – Key-points recap (1/2)

• Levels 1-3 of control → movement versatility.

• Task force dictates neural + energetic requirements.

Slide 29 – Key-points recap (2/2)

• Size principle central to graded recruitment & cost control.

• Precision inevitably declines with rising muscle-force demands.

Slide 30 – Closing visual & takeaway

• Graphic reinforces that with ↑contraction level:
  

  • Energy cost ↑

  • Control precision ↓

• Skill learning = shifting force-accuracy-economy curve to perform tasks with less ATP per Newton and tighter variability.

How to use these notes

• Map outcomes: tie each slide to the four learning outcomes when revising.

• Integrate physiology: link fibre-type properties (Slides 15-18) with metabolic modules from EXSS3071.

• Apply to practice: for rehab programming, exploit size-principle behaviour—start patients with low-force, high-precision drills, then layer in fast-unit recruitment as strength and tolerance develop.