Reward Reduces Motor Fatigability by Increasing Movement Vigour

This study demonstrates that the prospect of reward reduces motor slowing during sustained wrist tapping not by restoring movement efficiency, but by motivating participants to invest greater physical effort, as evidenced by increased muscle activation and sustained pupil dilation.

The Gist

The Big Idea: Can a "Carrot" Keep You Running When You're Tired?

Imagine you are running a marathon. About halfway through, your legs feel heavy, your pace slows down, and you just want to stop. This is motor fatigability—your body's natural tendency to slow down when you've been working hard for too long.

Now, imagine a friend starts running alongside you holding a giant, delicious carrot. Suddenly, you find a burst of energy and speed up again.

This study asked: Does a reward (like money or a prize) actually help people overcome physical fatigue, or does it just make them feel like they are trying harder?

The Experiment: The "Wrist Tapping" Race

The researchers put 25 healthy people in a lab to test this. Here's what they did:

1. The Task: Participants had to tap their wrists back and forth as fast as possible between two sensors for 40 seconds. It's like a very fast, repetitive drumming motion.
2. The Fatigue: After 20 seconds, everyone naturally started to slow down. Their taps got slower, just like a runner getting tired.
3. The Twist: At the 20-second mark, a signal appeared on the screen.
   • Neutral Signal: "Keep going." (No reward).
   • Reward Signal: "If you tap faster than you did in your last 'reward' round, you win 1 Swiss Franc!"

What They Found

1. The Reward Worked (The "Second Wind")
When the reward signal appeared, people immediately sped up. They tapped faster, almost returning to the speed they had at the very beginning of the test. The promise of a reward successfully fought off the feeling of fatigue.

2. But It Wasn't "Free" Energy (The Engine Analogy)
Here is the most interesting part. The researchers looked at the participants' muscles (using EMG sensors) and found that moving faster wasn't actually more efficient.

• The Analogy: Imagine your muscles are a car engine. When you are tired, the engine is sputtering.
  • The Old Theory: We thought the reward might "tune" the engine to run smoother and more efficiently.
  • The Reality: The reward didn't fix the engine. Instead, it told the driver to step harder on the gas pedal. The engine roared louder, burned more fuel, and worked harder to get the same (or slightly better) speed.
  • The Evidence: The muscles were working more intensely per tap when the reward was on the line. The body was paying a higher "energy tax" to move fast.

3. The Eyes Told the Truth (The "Effort Meter")
The researchers also tracked the size of the participants' pupils. Your pupils don't just react to light; they also react to mental and physical effort (like a gauge on a dashboard).

• When people were just tapping without a reward, their pupils slowly shrank as they got tired.
• When the reward appeared, their pupils dilated (got bigger) again.
• Crucially, this pupil dilation was bigger than what you would expect just from moving faster. It showed that the brain was saying, "I am willing to spend extra effort to get this reward."

The Conclusion: It's About "Accessing the Reserve Tank"

The study concludes that reward doesn't magically fix our tired muscles or make our movements more efficient. Instead, reward acts like a key that unlocks a "performance reserve."

When we are tired, our brain usually says, "We are running low on fuel, let's slow down to save energy."
But when a reward is introduced, the brain says, "Okay, we are low on fuel, but that prize is worth it. Let's open the emergency reserve tank, burn more fuel, and push through the pain."

In simple terms:
Reward doesn't make the work easier; it makes us willing to work harder to get the reward. It motivates us to accept a higher cost in energy to keep our speed up, even when our bodies are screaming to stop.

Why This Matters

This is great news for people with neurological conditions (like Multiple Sclerosis) where fatigue is a major problem. It suggests that motivational tools (like rewards, gamification, or positive feedback) could help these patients push through their fatigue and perform daily tasks better, not by fixing their muscles, but by helping their brains decide to "spend the extra energy" needed to get the job done.

Technical Summary

1. Problem Statement

Motor fatigability, defined as a reduction in motor performance during sustained or repetitive movements, is a prominent symptom in neurological disorders such as multiple sclerosis and Parkinson's disease. A specific manifestation of this is motor slowing, a gradual decline in movement speed over time during fast, repetitive tasks. While it is well-established that reward can enhance motor performance in non-fatigued states (by optimizing control or invigorating movement), it remains unclear whether reward can counteract fatigability-related motor slowing. Furthermore, the physiological mechanisms—specifically regarding muscle activity and effort investment (measured via pupil dilation)—underlying any potential reward-driven mitigation of fatigue are not fully understood.

2. Methodology

Participants and Design

• Sample: 25 healthy, right-handed participants (13 females, mean age 27 ± 4 years).
• Task: A wrist-tapping task performed at maximal voluntary speed between two force sensors for 40 seconds.
• Conditions: A within-subjects design with two conditions:
  • Neutral: No reward.
  • Reward: Participants could win 1 CHF if their average tapping speed over the 40s trial exceeded their speed in the previous reward trial.
• Procedure: Each trial consisted of a 5s baseline, a 40s tapping phase, and a 35s break. A visual cue appeared at the 20s mark to indicate whether the current trial was Neutral or Reward. The experiment included 20 trials (10 per condition).

Measurements

• Behavioral: Tapping frequency (Hz) derived from force sensor data.
• Physiological (EMG): Surface electromyography recorded from the Flexor Carpi Radialis (FCR) and Extensor Carpi Radialis Longus (ECR). Metrics included Area Under the Curve (AUC) of muscle envelopes and a coactivation index (overlap between antagonist muscles).
• Physiological (Pupillometry): Pupil diameter recorded at 60 Hz using an eye tracker. Pupil size serves as a proxy for physical effort and arousal (linked to the locus coeruleus-noradrenaline system).
• Controls: Dim ambient light, isoluminant stimuli to prevent light-driven pupil changes, and caffeine abstinence.

Data Analysis

• Statistical Modeling: Linear Mixed-Effects Models (LMEM) were used to analyze binned data (10s intervals: 0–10s, 10–20s, 20–30s, 30–40s) with fixed factors of Time, Condition, and their interaction.
• Time-Series Analysis: Non-parametric Statistical Parametric Mapping (SPM1D) was applied to continuous pupil data to identify specific time points of condition differences.
• Correlation: Robust correlation analyses examined the relationship between cue-evoked changes in tapping speed and pupil size.

3. Key Contributions

• Novelty in Fatigability: The study is among the first to demonstrate that reward can effectively attenuate motor slowing even when participants are already in a fatigued state.
• Mechanism of Action: It challenges the hypothesis that reward improves performance by "optimizing" motor control efficiency. Instead, it provides evidence that reward works by invigorating movement through increased resource mobilization, accepting higher energetic costs.
• Physiological Markers: The study integrates EMG and pupillometry to show that reward-induced performance gains are accompanied by increased muscle coactivation and sustained pupil dilation, indicating a shift in effort investment rather than efficiency.

4. Results

Behavioral Performance

• Motor Slowing: In the neutral condition, tapping frequency significantly declined over time (motor slowing was successfully induced).
• Reward Effect: Upon the presentation of the reward cue (at 20s), participants significantly increased their tapping speed, effectively reversing the slowing trend.
• Comparison: Post-cue tapping speeds in the reward condition were significantly faster than in the neutral condition and returned to levels comparable to the initial (pre-fatigue) speed.

Muscle Activity (EMG)

• Time Effect: Muscle activity (AUC) and coactivation increased over time in both conditions, indicating that movements became more energetically costly as fatigue set in.
• Reward Modulation: The reward cue significantly amplified this cost. Specifically, the FCR muscle activity and the coactivation index of the FCR/ECR pair were significantly higher in the reward condition compared to the neutral condition during the post-cue phase.
• Interpretation: Reward did not restore efficient motor control; rather, it led to a "costlier" execution where participants exerted more force/activation per tap to achieve higher speeds.

Pupil Dynamics

• Pattern: Pupil size initially dilated at movement onset, then gradually decreased (constricted) over time in the neutral condition.
• Reward Effect: In the reward condition, the reward cue triggered a significant re-dilation. Pupil size in the reward condition was significantly larger than in the neutral condition during the post-cue phase (20–40s).
• Covariate Analysis: Even after controlling for tapping speed, the reward condition still showed significantly larger pupil dilation. This suggests the dilation reflects increased effort investment and arousal beyond what is required simply to move faster.
• Correlation: There was a positive correlation between cue-evoked changes in tapping speed and pupil size in the reward condition, suggesting a link between the magnitude of effort mobilization and performance gain.

5. Significance and Conclusion

Mechanistic Insight
The findings suggest that reward mitigates motor fatigability not by repairing the underlying inefficiencies of the fatigued motor system, but by allowing individuals to access a performance reserve. Participants mobilize additional central resources (likely mediated by the noradrenergic locus coeruleus system, as inferred from pupil data) to drive the motor output harder, accepting higher energetic costs (increased coactivation) to maintain speed.

Clinical and Practical Implications

• Neurological Rehabilitation: These results suggest that motivational interventions (e.g., reward-based therapy) could be highly effective for patients with neurological conditions characterized by excessive motor fatigability (e.g., Multiple Sclerosis). By leveraging reward, clinicians might help patients overcome performance declines without necessarily fixing the peripheral or central fatigue mechanisms.
• Effort-Performance Trade-off: The study highlights a trade-off where performance is maintained at the expense of increased physiological cost, mediated by arousal and effort investment.

Limitations & Future Directions
While the study strongly implicates the LC-NA system via pupillometry, direct neural evidence (e.g., fMRI or pharmacological manipulation) is needed to confirm the specific neuromodulatory pathways. Future research should explore how these mechanisms differ in clinical populations.