Bayesian inference as the basis of sense of agency

• Applicants: Professor Dr. David Franklin; Professor Dr. Mathias Hegele
• Subject Area: Human Cognitive and Systems Neuroscience ; Biological Psychology and Cognitive Neuroscience
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 467042759

The sense of agency is the feeling we get that we are the acting agent that is responsible for any changes in the state of our body or the environment. Experimental studies from psychology, cognitive neuroscience and motor control have established a close link between the sense of agency and the predictability of the sensory consequences of our own actions. Based on the comparison between predicted and actual action outcome, it is decided whether we were responsible for a perceived event or not. However, contradicting evidence of this ‘comparator model’, such as when external cues regarding the agent appear prior to the movement or when there are temporal discrepancies between the movement and sensory feedback, suggest that this simple comparison cannot account for the core mechanism responsible for the sense of agency. Alternatively, it was suggested that humans also take into account prior beliefs regarding the acting agent and integrate this information with the likelihood that we were responsible for the observed outcome when forming the self-agency sensation. While this Bayesian integration framework is considered as a powerful computational approach to explain how the sense of agency is formed, there are limited experimental designs that tackle the core characteristics of this framework in order to support it.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.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2134: The active self