A most basic form of human social interaction is the physical cooperation necessary to perform a manual task in pairs (dyads) or groups. This project will explore how the human sensorimotor control system implements cooperative motor control. In preliminary work, the project team has demonstrated that when a dyad embarks on a repeated simple manual task requiring speed and accuracy, motor strategies quickly arise that not only differ significantly from individual strategies on the same task, but also provide better performance. This result runs counter to conventional wisdom that high accuracy tasks are best performed by one individual alone. Nevertheless, from both evolutionary and ontological perspectives, the result is reasonable: humans are social animals and have developed sophisticated ways of working together physically. Motor interactions represent a social communication mechanism distinct from facial expression, gesture, and spoken language.
The project team encompasses cognitive science, neurobiology, robotics, and sensorimotor control, and will:
Investigate the language of physical communication between two or more individuals as they develop a cooperative strategy to perform a mechanical task. Identify channels of this communication, for instance modulation of arm stiffness. Investigate the adaptation that underlies the emergence of cooperative behaviors during physical communication, as the participants negotiate, compromise, specialize, teach and learn, or in some other way arrive at an effective cooperative behavior.
Investigate cognitive influences on cooperative behaviors. Determine the extent to which the cooperative behaviors reflect cognitive influences on motor control, as opposed to implicit or inherent biomechanical properties of the sensorimotor system.
Investigate the emergent behaviors as specifically social phenomena. Assess their extension to groups sizes of more than two, and the social aspects of adaptation, such as the effect of errors or "breaches of trust." Investigate the substitution of an automated partner (robot) for a human partner.
Investigate the factors at the sensorimotor level that allow dyadic motion control to optimize performance better than individual motor control. Hypotheses include reduction in delays associated with the triphasic burst pattern of muscle activation, and the partitioning of motor noise into separate spaces.
Broader impacts include: improving our fundamental understanding of therapist/patient interactions during physical or occupational therapy, many aspects of which are repetitive dyadic physical interaction. The work may also lead to better ways to make use of the social dynamics between individuals in physical interaction, which would be relevant to situations such as hands-on teaching/learning a in sports training or helicopter flight training, shared control of teleoperators or of unmanned aerial or underwater vehicles, and shared control of minimally invasive surgery or telesurgery.
