Brain Signatures of Time Perception in Virtual Reality.

Sahar Niknam, Saravanakumar Duraisamy, Jean Botev, Luis A Leiva
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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.

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要在虚拟现实(VR)中实现高水平的沉浸感和适应性,需要精确测量和呈现用户状态。虽然运动和姿势等外在物理特征可以被实时精确地跟踪,但可靠地捕捉心理状态则更具挑战性。定量心理学允许考虑更多内在特征,如情绪、注意力或认知负荷。时间感知尤其与用户的心理状态密切相关,包括压力、注意力和无聊感。然而,客观测量我们感知时间流逝的速度的研究却很少。在这项工作中,我们研究了脑电图(EEG)作为 VR 中时间感知客观测量方法的潜力,探索了振荡响应和时间频率分析的神经相关性。为此,我们在 VR 中实施了多种时间感知调节器,收集了脑电图记录,并将其标记为高估、正确估计和低估时间感知状态。我们发现这三种状态都有明显的脑电图频谱特征,而且在不同的个体、调制器和调制持续时间中都会持续存在。这些特征可以整合并应用于监测和积极影响 VR 中的时间感知,从而使虚拟环境有目的地适应个人,进一步增强沉浸感,改善用户体验。本文及所有补充材料的免费拷贝可从 https://vrarlab.uni.lu/pub/brain-signatures 网站获取。
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