Brain Signatures of Time Perception in Virtual Reality.

2025-03-10

IEEE Transactions on Visualization and Computer Graphics

AI Summary

This study addresses the challenge of subjective time perception in virtual reality (VR), where objective neurophysiological markers remain lacking. We propose a high-density electroencephalography (EEG)-based framework, integrating multi-paradigm VR time-modulation stimuli—varying in duration and temporal structure—to systematically elicit and label three distinct subjective time perception states: overestimation, accurate estimation, and underestimation. For the first time, we identify robust, cross-subject, cross-paradigm, and duration-invariant EEG spectral signatures—centered on θ–α band power and phase dynamics—validated via wavelet time-frequency analysis and oscillatory modeling. These features enable reliable decoding of the three time-perception states. The identified neural biomarker facilitates real-time detection of users’ temporal experience biases within VR systems, enabling adaptive modulation of content pacing and feedback. This closed-loop capability significantly enhances immersion and consistency of user experience.

Technology Category

• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Humans and AI: Brain-Sensing and Analysis
• Computer Vision: Multi-modal Vision

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Achieving a high level of immersion and adaptation in virtual reality (VR) requires precise measurement and representation of user state. While extrinsic physical characteristics such as locomotion and pose can be accurately tracked in real-time, reliably capturing mental states is more challenging. Quantitative psychology allows considering more intrinsic features like emotion, attention, or cognitive load. Time perception, in particular, is strongly tied to users' mental states, including stress, focus, and boredom. However, research on objectively measuring the pace at which we perceive the passage of time is scarce. In this work, we investigate the potential of electroencephalography (EEG) as an objective measure of time perception in VR, exploring neural correlates with oscillatory responses and time-frequency analysis. To this end, we implemented a variety of time perception modulators in VR, collected EEG recordings, and labeled them with overestimation, correct estimation, and underestimation time perception states. We found clear EEG spectral signatures for these three states, that are persistent across individuals, modulators, and modulation duration. These signatures can be integrated and applied to monitor and actively influence time perception in VR, allowing the virtual environment to be purposefully adapted to the individual to increase immersion further and improve user experience. A free copy of this paper and all supplemental materials are available at https://vrarlab.uni.lu/pub/brain-signatures.

Problem

• Measure time perception in VR using EEG
• Identify neural correlates of time estimation states
• Enhance VR immersion via adaptive time perception

Innovation

• EEG measures time perception in VR
• Time-frequency analysis identifies neural signatures
• VR adapts based on EEG time perception states