Bayesian inference as the basis of sense of agency

Forming the sense of agency is believed to follow a Bayesian integration framework. That is, during interaction with the environment, humans take into account prior beliefs regarding the acting agent and integrate this information with the likelihood that they were responsible for the observed outcome.

Here we will directly test the predictions of the Bayesian integration framework when forming the sense of agency. Through a series of psychophysical experiments we test participants’ sense of agency while manipulating the prior beliefs and the sensory feedback using haptic robots integrated in a virtual reality environments. These experiments focus on the formation of the sense of agency during different object manipulation tasks in the presence of a virtual external agent that acts at different magnitudes and under different uncertainties. Each experiment is designed to control the effect of a single contributor in the integration framework while keeping the other factors unaffected. Our results will assist in developing a model of active self for use in robotics, and may also be critical for developing control of assistive robotics (such as rehabilitation robots) and human-robot interactions where the sense of self agency is important for rehabilitation success and successful collaboration.

PIs: Prof. Dr.  David Franklin

Postdocs: Dr. Raz Leib

PhD Students: Clara Günter