Vision and Control of Action Group, Department of Cognition, Development, and Psychology of Education, Institute of Neurosciences, Universitat de Barcelona, Barcelona, Catalonia, Spain.
J Vis. 2024 Jun 3;24(6):14. doi: 10.1167/jov.24.6.14.
Accurately estimating time to contact (TTC) is crucial for successful interactions with moving objects, yet it is challenging under conditions of sensory and contextual uncertainty, such as occlusion. In this study, participants engaged in a prediction motion task, monitoring a target that moved rightward and an occluder. The participants' task was to press a key when they predicted the target would be aligned with the occluder's right edge. We manipulated sensory uncertainty by varying the visible and occluded periods of the target, thereby modulating the time available to integrate sensory information and the duration over which motion must be extrapolated. Additionally, contextual uncertainty was manipulated by having a predictable and unpredictable condition, meaning the occluder either reliably indicated where the moving target would disappear or provided no such indication. Results showed differences in accuracy between the predictable and unpredictable occluder conditions, with different eye movement patterns in each case. Importantly, the ratio of the time the target was visible, which allows for the integration of sensory information, to the occlusion time, which determines perceptual uncertainty, was a key factor in determining performance. This ratio is central to our proposed model, which provides a robust framework for understanding and predicting human performance in dynamic environments with varying degrees of uncertainty.
准确估计接触时间 (TTC) 对于与移动物体的成功交互至关重要,但在感官和上下文不确定的情况下,例如遮挡,这是具有挑战性的。在这项研究中,参与者参与了一个预测运动任务,监测向右移动的目标和一个遮挡物。参与者的任务是在他们预测目标将与遮挡物的右边缘对齐时按下一个键。我们通过改变目标的可见和遮挡期来操纵感官不确定性,从而调节了整合感官信息的可用时间和必须外推的运动持续时间。此外,通过有可预测和不可预测的条件来操纵上下文不确定性,这意味着遮挡物要么可靠地指示移动目标将消失的位置,要么不提供任何指示。结果显示,在可预测和不可预测的遮挡物条件下,准确性存在差异,每种情况下的眼动模式也不同。重要的是,目标可见的时间与确定感知不确定性的遮挡时间之比是决定表现的关键因素。这个比例是我们提出的模型的核心,它为理解和预测具有不同程度不确定性的动态环境中的人类表现提供了一个强大的框架。