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

Area of Science:

• Neuroscience
• Motor Control
• Human Physiology

Background:

• Many real-world tasks require impedance control to minimize motion error.
• Existing human motor optimization studies focus on tasks with a single error-effort optimum.
• These studies often assume increased impedance leads to optimal performance.

Purpose of the Study:

• To investigate motor optimization in tasks with multiple solutions and potential optima.
• To introduce a novel paradigm for exploring how multiple solutions affect motor behavior.
• To understand the role of motor memory in suboptimal task performance.

Main Methods:

• Developed a novel experimental paradigm to allow subjects to repetitively use different task solutions.
• Subjects performed tasks with multiple solutions, allowing for observation of motor behavior.
• Inconspicuously varied task solutions to study their impact on motor learning and adaptation.

Main Results:

• Motor behavior is significantly influenced by motor memory.
• Subjects tended to repeat recent suboptimal solutions, even after experiencing the optimal one.
• This suggests a tradeoff between motor memory, error minimization, and effort minimization.

Conclusions:

• The central nervous system (CNS) may not globally optimize co-activation tasks.
• Motor behavior determination involves a complex tradeoff, including motor memory.
• Suboptimal solutions can persist due to the influence of motor memory in motor control.