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Neural Research on Depth Perception and Stereoscopic Visual Fatigue in Virtual Reality

Mei Guo, Kang Yue, Haochen Hu, Kai Lü, Yu Han, Shanshan Chen, Yue Liu

2022Brain Sciences18 citationsDOIOpen Access PDF

Abstract

Virtual reality (VR) technology provides highly immersive depth perception experiences; nevertheless, stereoscopic visual fatigue (SVF) has become an important factor currently hindering the development of VR applications. However, there is scant research on the underlying neural mechanism of SVF, especially those induced by VR displays, which need further research. In this paper, a Go/NoGo paradigm based on disparity variations is proposed to induce SVF associated with depth perception, and the underlying neural mechanism of SVF in a VR environment was investigated. The effects of disparity variations as well as SVF on the temporal characteristics of visual evoked potentials (VEPs) were explored. Point-by-point permutation statistical with repeated measures ANOVA results revealed that the amplitudes and latencies of the posterior VEP component P2 were modulated by disparities, and posterior P2 amplitudes were modulated differently by SVF in different depth perception situations. Cortical source localization analysis was performed to explore the original cortex areas related to certain fatigue levels and disparities, and the results showed that posterior P2 generated from the precuneus could represent depth perception in binocular vision, and therefore could be performed to distinguish SVF induced by disparity variations. Our findings could help to extend an understanding of the neural mechanisms underlying depth perception and SVF as well as providing beneficial information for improving the visual experience in VR applications.

Topics & Concepts

Virtual realityStereoscopyPerceptionDepth perceptionComputer scienceStereopsisVisual cortexVisual perceptionPsychologyNeuroscienceComputer visionHuman–computer interactionVisual perception and processing mechanismsOcular and Laser Science ResearchAdvanced Optical Imaging Technologies