Motor memory and local minimization of error and effort, not global optimization, determine motor behavior

Area of Science:

• Neuroscience
• Motor Control
• Biomechanics

Background:

• Many real-world tasks necessitate impedance control to minimize motion error.
• These tasks often present multiple solutions, balancing muscle co-contraction (high effort) against muscle relaxation (low effort).
• Existing human motor optimization research primarily examines tasks with a single error-effort optimum, typically achieved by increasing impedance.

Purpose of the Study:

• To investigate motor optimization strategies when multiple solutions exist.
• To introduce a novel experimental paradigm for exploring these multiple solutions.
• To observe the impact of exploring diverse solutions on motor behavior.

Main Methods:

• Developed a novel experimental paradigm to allow subjects to repetitively and inconspicuously utilize different task solutions.
• Subjects performed tasks with multiple solutions, enabling observation of motor behavior during exploration.
• Analyzed the influence of motor memory on solution selection over time.

Main Results:

• Motor behavior was significantly influenced by motor memory.
• Subjects tended to involuntarily repeat recent, suboptimal solutions, even after experiencing the optimal one.
• This indicates a deviation from global optimization in co-activation tasks.

Conclusions:

• The central nervous system (CNS) may not globally optimize co-activation tasks.
• Motor behavior appears to be determined by a trade-off between motor memory, error minimization, and effort minimization.
• Motor memory plays a crucial role in perpetuating suboptimal solutions in tasks with multiple solutions.