The project "Plasticity of body representation of self and other in collaborative tasks" (SOLAR, opens an external URL in a new window) is part of the DFG Priority Program "The Active Self", opens an external URL in a new window.

In (con-)joint activities, such as lifting and moving an object, interpersonal coordination is a primary requirement. Moving as a coordinated unit is not likely to succeed at first, as we may fail in predicting the partner’s dynamic capabilities by overgeneralizing from representations such as our own body schema. Subsequent coordination attempts, however, may gradually improve our predictions of our partner’s action space. We argue therefore that by repeated exposure to the movement dynamics of a partner in a joint action task, we will learn to predict their dynamics and generate a body schema representation of the confederate. Thus, we consider mechanisms responsible for the minimization of prediction error crucial to the experience-dependent adjustment of self-representations as well as the acquisition of partner representations, which facilitate the distinction between the influence of self and other with respect to the concurrent demands of the joint task.

In order to research the plasticity of self and partner representations, this project will investigate collaborative learning that occurs in a goal-directed joint dexterity task. Changes in performance will be correlated with altered representations during and following training sessions, in which pairs are practicing a “collaborative hotwire” task, which is a simulated object transporting task, under several levels of spatiotemporal difficulty. In addition to measurements of movements and interaction forces and torques, our project will assess participants’ representations of self and partner. For example, body schema and body image, but also sense of agency as a function of leader-follower relationships and self-other-overlap will be recorded during and after joint practice. Using human-human collaboration as a performance benchmark, we will apply the paradigm to human-robot-collaborations aiming not only to simulate collaborative performance and acquisition of representations of self and other, but also to test the quality of robotic control models in the form of a joint action “Turing test”.