Prediction error and regularity detection underlie two dissociable mechanisms for computing the sense of agency.

The sense of agency refers to the subjective feeling of controlling one's own actions, and through them, events in the outside world. According to computational motor control models, the prediction errors from comparison between the predicted sensory feedback and actual sensory feedback determine whether people feel agency over the corresponding outcome event, or not. This mechanism requires a model of the relation between action and outcome. However, in a novel environment, where this model has not yet been learned, the sense of agency must emerge during exploratory behaviours. In the present study, we designed a novel control detection task, in which participants explored the extent to which they could control the movement of three dots with a computer mouse, and then identified the dot that they felt they could control. Pre-recorded motions were applied for two dots, and the participants' real-time motion only influenced one dot's motion (i.e. the target dot). We disturbed participants' control over the motion of the target dot in one of two ways. In one case, we applied a fixed angular bias transformation between participant's movements and dot movements. In another condition, we mixed the participant's current movement with replay of another movement, and used the resulting hybrid signal to drive visual dot position. The former intervention changes the match between motor action and visual outcome, but maintains a regular relation between the two. In contrast, the latter alters both matching and motor-visual correlation. Crucially, we carefully selected the strength of these two perturbations so that they caused the same magnitude of impairment of motor performance in a simple reaching task, suggesting that both interventions produced comparable prediction errors. However, we found the visuomotor transformation had much less effect on the ability to detect which dot was under one's own control than did the nonlinear disturbance. This suggests a specific role of a correlation-like mechanism that detects ongoing visual-motor regularity in the human sense of agency. These regularity-detection mechanisms would remain intact under the linear, but not the nonlinear transformation. Human sense of agency may depend on monitoring ongoing motor-visual regularities, as well as on detecting prediction errors.