Abstract:
In our daily lives, we encounter various sensorimotor events, in which sensory perception
and actions are intertwined. The sense of agency for a given action refers to the sense of
authorship regarding that action. Computational models of motor control suggest that
prediction of sensory information by internal models is matched against subsequent
sensory information. If predicted and sensed information match, then the sensory events
are self-generated, and the subject experiences a sense of agency for those events. If there is
mismatch, then subjects attribute the outcome to an external cause/agent. Central feedback
mechanisms play significant roles in the motor control and self-attribution of agency.
Previously, we found that external feedback about the action can alter the attribution of
agency before assimilating the actual sensory consequences, by updating motor predictions
in real-time.