University of Leicester, School of Psychology and Vision Sciences, United Kingdom.
University of Leicester, School of Psychology and Vision Sciences, United Kingdom.
Hum Mov Sci. 2023 Oct;91:103126. doi: 10.1016/j.humov.2023.103126. Epub 2023 Jul 28.
Smooth pursuit eye movements are mainly driven by motion signals to achieve their goal of reducing retinal motion blur. However, they can also show anticipation of predictable movement patterns. Oculomotor predictions may rely on an internal model of the target kinematics. Most investigations on the nature of those predictions have concentrated on simple stimuli, such as a decontextualized dot. However, biological motion is one of the most important visual stimuli in regulating human interaction and its perception involves integration of form and motion across time and space. Therefore, we asked whether there is a specific contribution of an internal model of biological motion in driving pursuit eye movements. Unlike previous contributions, we exploited the cyclical nature of walking to measure eye movement's ability to track the velocity oscillations of the hip of point-light walkers. We quantified the quality of tracking by cross-correlating pursuit and hip velocity oscillations. We found a robust correlation between signals, even along the horizontal dimension, where changes in velocity during the stepping cycle are very subtle. The inversion of the walker and the presentation of the hip-dot without context incurred the same additional phase lag along the horizontal dimension. These findings support the view that information beyond the hip-dot contributes to the prediction of hip kinematics that controls pursuit. We also found a smaller phase lag in inverted walkers for pursuit along the vertical dimension compared to upright walkers, indicating that inversion does not simply reduce prediction. We suggest that pursuit eye movements reflect the visual processing of biological motion and as such could provide an implicit measure of higher-level visual function.
平滑追踪眼球运动主要由运动信号驱动，以实现减少视网膜运动模糊的目标。然而，它们也可以显示对可预测运动模式的预期。眼动预测可能依赖于目标运动学的内部模型。大多数关于这些预测本质的研究都集中在简单的刺激上，例如去语境化的点。然而，生物运动是调节人类互动的最重要的视觉刺激之一，其感知涉及形式和运动在时间和空间上的整合。因此，我们想知道是否有一种特定的生物运动内部模型对追踪眼球运动有贡献。与以前的贡献不同，我们利用步行的周期性来测量眼球运动跟踪点光步行者臀部速度振荡的能力。我们通过交叉相关来量化跟踪的质量追踪和臀部速度振荡。我们发现信号之间存在很强的相关性，即使在水平方向上，因为在步幅周期中速度的变化非常微妙。步行者的反转和臀部点的呈现没有上下文，在水平方向上产生相同的附加相位滞后。这些发现支持了这样一种观点，即除了臀部点之外的信息有助于控制追踪的臀部运动学预测。我们还发现，与直立步行者相比，倒立步行者在垂直方向上的追踪相位滞后较小，这表明反转并不仅仅减少了预测。我们认为，追踪眼球运动反映了对生物运动的视觉处理，因此可以提供对更高层次视觉功能的隐含测量。
