Optimal control of reaching includes kinematic constraints.

Area of Science:

• Motor control
• Robotics
• Biomechanics

Background:

• Reaching movements are fundamental to human motor control.
• Adaptation to force field perturbations reveals underlying motor control strategies.
• Previous models often prioritize accuracy and effort minimization.

Purpose of the Study:

• To investigate adaptation in reaching movements under a novel acceleration-based force field.
• To determine if motor control prioritizes kinematic invariance over motor effort.
• To model reaching behavior using stochastic optimal control theory.

Main Methods:

• Participants performed a reaching task with an acceleration-based force field.
• Behavioral data on hand trajectories were analyzed.
• Stochastic optimal control theory was used to model the observed adaptation.

Main Results:

• Subjects showed a directional preference, adapting curved trajectories towards their initial straight baselines.
• This adaptation occurred despite a strategy that would minimize motor effort by deviating from a straight path.
• The results indicate a trade-off between target accuracy, motor effort, and kinematic invariance.

Conclusions:

• Robustness, particularly against internal model uncertainty, is essential for reaching movements.
• Kinematic invariance plays a significant role in the objective function of reaching.
• The findings challenge assumptions that solely focus on accuracy and energy efficiency in motor control models.