Exploring Depth-based Perception Conflicts in Virtual Reality through Error-Related Potentials

Virtual Reality (VR) offers a valuable platform for real-life skills training. However, previous research has indicated that human's perception of depth in VR differs from that of the real world. Such perceptual conflicts can impact immersion and the learning of skills, thus attracting widespread attention. Various methods have been proposed to enhance users' depth perception, yet the underlying mechanisms of depth perception conflicts still require further research. In this paper, we used Error-Related Potentials (ErrPs) from electroencephalography (EEG) data to investigate the differences in participants' perceptions at varying depths within the near-field. We designed a within-subjects experiment to successfully introduce depth perception conflicts. From participants exposed to three distinct depths, we collected questionnaire results, performance data, and EEG data. Our findings showed that EEG can effectively detect depth perception conflicts and, following each conflict, participants' behavioral patterns showed significant changes. In situations with shallower depths, participants exhibited stronger responses to the designed conflicts. This increased sensitivity correlates with their accuracy in depth estimation. This study represents a novel approach to depth perception in VR using ErrPs, setting the stage for further use of physiological signals to measure the granularity of depth perception in VR/AR environments.