Evidence for the flexible sensorimotor strategies predicted by optimal feedback control

Area of Science:

• Motor control
• Neuroscience
• Biomechanics

Background:

• Traditional theories of movement control focus on geometry and servo control, often overlooking task-specific strategies.
• Optimal feedback control theory emphasizes the relationship between task goals and movement strategies.

Purpose of the Study:

• To investigate how sensorimotor strategies are customized for diverse and conflicting task goals.
• To explain psychophysical findings, such as incomplete late corrections in reaching movements, using optimal feedback control.
• To explore the trade-off between stability and accuracy in motor control.

Main Methods:

• Developed an optimal feedback control model incorporating composite cost functions.
• Analyzed optimal feedback gains to identify trade-offs between stability and accuracy.
• Conducted experiments in 3D obstacle avoidance and interception tasks with a programmable robotic target.

Main Results:

• Incomplete late corrections in reaching movements are explained by a stability-accuracy trade-off, not just lack of time.
• Decreased stability requirements led to increased accuracy, confirming theoretical predictions.
• Subjects demonstrated flexible control strategies, optimizing performance by exploiting opportunities.

Conclusions:

• Motor behavior's flexibility arises from sensorimotor control laws optimized for composite cost functions.
• Optimal feedback control provides a framework for understanding task-specific motor adaptation.
• The findings challenge traditional models and highlight the dynamic nature of motor coordination.