Energy constraints determine the selection of reaching movement trajectories in macaque monkeys.

Abstract

Reaching movements, while seemingly simple, involve complex motor control mechanisms that select specific trajectories from infinite possibilities. Despite the inherent variability in volitional movements, both humans and monkeys frequently exhibit stereotyped trajectories. The literature has offered numerous explanations for invariant trajectory shapes, including a common planning space in hand-space or joint-space, as well as factors like kinetic energy (KE) minimization and sensory feedback. However, since most studies have relied on single-session data, crucial insights into the motor principles guiding trajectory selection and their evolution through extended practice remain underexplored. This study fills this gap by investigating how specific trajectories are selected and evolve with practice across multiple sessions, using data from two rhesus monkeys (one male, one female) performing a reaching task in a biomechanically constrained 2D setup. Our behavioral study challenges the idea of a common planning space, revealing instead a significant influence of KE on trajectory shapes. Through a novel biomechanical modeling, we quantified KE for a wide range of trajectory shapes. We discovered that trajectory selection and evolution is not simply about minimizing KE or achieving straight paths. Instead, the monkeys' motor systems appear to prioritize maintaining a "safe KE range," where slight changes in trajectory shapes have minimal impact on energy expenditure. These findings provide new insights into the adaptive motor control strategies, suggesting that trajectory selection involves balancing energy efficiency and flexibility. Our study enhances the understanding of trajectory selection principles, with implications for rehabilitation strategies, robotics and broader study of motor control mechanisms.Significance statement This study provides new insights into motor control by analyzing and modeling monkey behavior, revealing that kinetic energy (KE) significantly influences trajectory shape. Our findings challenge the conventional views that trajectory selection primarily aims to maximize straightness or minimize KE. Instead, our analyses show that the motor system seeks to maintain a "safe KE range," where small trajectory differences do not significantly impact energy expenditure. We reach this conclusion through a novel biomechanical modeling approach, which quantifies KE across a wide range of trajectory shapes for specific movements. By combining behavioral analysis with modeling, we demonstrate that trajectory selection balances efficiency and flexibility, offering valuable implications for developing rehabilitation strategies and robotic assistive devices that align with natural movement principles.