Drifting perceptual patterns suggest prediction errors fusion rather than hypothesis selection: replicating the rubber-hand illusion on a robot

Abstract

Humans can experience fake body parts as theirs just by simple visuo-tactile synchronous stimulation. This bodyillusion is accompanied by a drift in the perception of the real limb towards the fake limb, suggesting an update of body estimation resulting from stimulation. This work compares body limb drifting patterns of human participants, in a rubber hand illusion experiment, with the end-effector estimation displacement of a multisensory robotic arm enabled with predictive processing perception. Results show similar drifting patterns in both human and robot experiments, and they also suggest that the perceptual drift is due to prediction error fusion, rather than hypothesis selection. We present body inference through prediction error minimization as one single process that unites predictive coding and causal inference and that it is responsible for the effects in perception when we are subjected to intermodal sensory perturbations.

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“…Another concern is related to the "proprioceptive drift" as the classic "objective measure" for the RHI, as used in the experiment mentioned above [51]. Both the human data from this study, as well as previous work in humans [53], [54], failed to find a correlation between the proprioceptive drift and the self-report of the participants, casting doubt on the validity of the proprioceptive drift as an objective measure for body ownership.…”

“…When humans are subjected to the RHI, they show a perceptual drift in the location of the real hand toward the dummy hand, which suggests an update in the body representation. Using a multisensory robotic arm, Hinz et al [51] replicated these drifting patterns in both human and robot experiments with the classic ("passive") RHI paradigm. The learning and estimation algorithm [52] used in the study was based on the framework of predictive coding [21].…”

“…They modeled the robot body estimation as a process of minimizing the prediction error between the body configuration "belief" (prediction) and the observed posterior, and minimizing the variational free energy [21] by using the sensory prediction error. Using the algorithm in [52], Hinz et al [51] showed that body configuration estimation can be done through minimization of prediction error as one process that involves both predictive coding and causal inference. The results from the human and robot experiments suggest that the perceived locations of both the real and the dummy hand drift to a common location between them.…”

“…However, the investigation on RHI experienced by artificial systems is very scarce. To the best of our knowledge, the work of Hinz et al [51] is the only study on replicating the rubber hand illusion on a robot.…”

“…Further investigation is therefore suggested. Also, after reproducing the classic, "passive" RHI in a robot using free energy minimization [51], it could be suggested to examine the algorithm in an "active" RHI experimental setup, which would allow to distinctly examine sense of agency in a robot apart from body ownership.…”