Inferring control objectives in a virtual balancing task in humans and monkeys

• Published in: eLife Vol. 12
• Main Authors: Sadeghi, Mohsen, Sharif Razavian, Reza, Bazzi, Salah, Chowdhury, Raeed H, Batista, Aaron P, Loughlin, Patrick J, Sternad, Dagmar
• Format: Journal Article
• Language: English
• Published: England eLife Sciences Publications Ltd 13.05.2024; eLife Sciences Publications, Ltd
• Subjects: Adult; Animals; Behavior; Behavior, Animal - physiology; Control algorithms; feedback-driven behavior; Female; human monkey comparison; Humans; Kinematics; Macaca mulatta; Male; Monkeys & apes; Motion capture; motor control strategies; Neuroscience; Objectives; optimal feedback control; Postural Balance - physiology; Primates; Psychomotor Performance - physiology; Sensorimotor system; Velocity; vsuomotor control; Young Adult; motor control strategies; human monkey comparison; rhesus macaque; feedback-driven behavior; neuroscience; optimal feedback control; human; vsuomotor control
• ISSN: 2050-084X; 2050-084X
• DOI: 10.7554/eLife.88514

Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different strategies. Given only observations of behavior, is it possible to infer the control objective that the subject is employing? This challenge is particularly acute in animal behavior because we cannot ask or instruct the subject to use a particular strategy. This study presents a three-pronged approach to infer an animal’s control objective from behavior. First, both humans and monkeys performed a virtual balancing task for which different control strategies could be utilized. Under matched experimental conditions, corresponding behaviors were observed in humans and monkeys. Second, a generative model was developed that represented two main control objectives to achieve the task goal. Model simulations were used to identify aspects of behavior that could distinguish which control objective was being used. Third, these behavioral signatures allowed us to infer the control objective used by human subjects who had been instructed to use one control objective or the other. Based on this validation, we could then infer objectives from animal subjects. Being able to positively identify a subject’s control objective from observed behavior can provide a powerful tool to neurophysiologists as they seek the neural mechanisms of sensorimotor coordination.