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With Motor imagery (MI), movements are mentally rehearsed without overt actions; this procedure has been adopted in motor rehabilitation, primarily in brain-damaged patients. Here we rather tested the clinical potentials of MI in purely orthopaedic patients who, by definition, should maximally benefit of mental exercises because of their intact brain. To this end we studied the recovery of gait after total knee arthroplasty and evaluated whether MI combined with physiotherapy could speed up the recovery of gait and even limit the occurrence of future falls. We studied 48 patients at the beginning and by the end of the post-surgery residential rehabilitation program: half of them completed a specific MI training supported by computerized visual stimulation (experimental group); the other half performed a non-motoric cognitive training (control group). All patients also had standard physiotherapy. By the end of the rehabilitation, the experimental group showed a better recovery of gait and active knee flexion-extension movements, and less pain. The number of falls or near falls after surgery was significantly lower in the experimental group. These results show that MI can improve gait abilities and limit future falls in orthopaedic patients, without collateral risks and with limited costs.

What is the key to successful interaction? Is it sufficient to represent a common goal, or does the way our partner achieves that goal count as well? How do we react when our partner misbehaves? We used a turn-taking music-like task requiring participants to play sequences of notes together with a partner, and we investigated how people adapt to a partner’s error that violates their expectations. Errors consisted of either playing a wrong note of a sequence that the agents were playing together (thus preventing the achievement of the joint goal) or playing the expected note with an unexpected action. In both cases, we found post-error slowing and inaccuracy suggesting the participants’ implicit tendency to correct the partner’s error and produce the action that the partner should have done. We argue that these “joint” monitoring processes depend on the motor predictions made within a (dyadic) motor plan and may represent a basic mechanism for mutual support in motor interactions.

What mechanisms distinguish interactive from non-interactive actions? To answer this question we tested participants while they took turns playing music with a virtual partner: in the interactive joint action condition, the participants played a melody together with their partner by grasping (C note) or pressing (G note) a cube-shaped instrument, alternating in playing one note each. In the non-interactive control condition, players’ behavior was not guided by a shared melody, so that the partner’s actions and notes were irrelevant to the participant. In both conditions, the participant’s and partner’s actions were physically congruent (e.g., grasp-grasp) or incongruent (e.g., grasp-point), and the partner’s association between actions and notes was coherent with the participant’s or reversed. Performance in the non-interactive condition was only affected by physical incongruence, whereas joint action was only affected when the partner’s action-note associations were reversed. This shows that task interactivity shapes the sensorimotor coding of others’ behaviors, and that joint action is based on active prediction of the partner’s action effects rather than on passive action imitation. We suggest that such predictions are based on Dyadic Motor Plans that represent both the agent’s and the partner’s contributions to the interaction goal, like playing a melody together.