Cognitive Science, Department of Digital Humanities & Helsinki Centre for Digital Humanities (Heldig), University of Helsinki, Helsinki, Finland.
TRUlab, University of Helsinki, Helsinki, Finland.
Sci Rep. 2020 Mar 6;10(1):4175. doi: 10.1038/s41598-020-60531-3.
It is well-established how visual stimuli and self-motion in laboratory conditions reliably elicit retinal-image-stabilizing compensatory eye movements (CEM). Their organization and roles in natural-task gaze strategies is much less understood: are CEM applied in active sampling of visual information in human locomotion in the wild? If so, how? And what are the implications for guidance? Here, we directly compare gaze behavior in the real world (driving a car) and a fixed base simulation steering task. A strong and quantifiable correspondence between self-rotation and CEM counter-rotation is found across a range of speeds. This gaze behavior is "optokinetic", i.e. optic flow is a sufficient stimulus to spontaneously elicit it in naïve subjects and vestibular stimulation or stereopsis are not critical. Theoretically, the observed nystagmus behavior is consistent with tracking waypoints on the future path, and predicted by waypoint models of locomotor control - but inconsistent with travel point models, such as the popular tangent point model.
视觉刺激和实验室条件下的自身运动可靠地引起视网膜图像稳定的补偿性眼球运动（CEM），这一点已经得到充分证实。然而，它们在自然任务注视策略中的组织和作用还不太清楚：在人类自然运动中，CEM 是否被应用于主动采样视觉信息？如果是，如何应用？这对引导有什么影响？在这里，我们直接比较了现实世界（开车）和固定基座模拟转向任务中的注视行为。在一系列速度下，发现自身旋转和 CEM 反向旋转之间存在很强且可量化的对应关系。这种注视行为是“视动性的”，即光流是一种充分的刺激，可以在未经训练的受试者中自发地引起它，而前庭刺激或立体视觉并不是关键因素。从理论上讲，观察到的眼球震颤行为与跟踪未来路径上的航点一致，并可由运动控制的航点模型预测，但与旅行点模型不一致，例如流行的切线点模型。
