Investigating and modeling the perception of self-motion in the presence of independent object motion and the simultaneous perception of object motion with visual and non-visual cues

在独立运动的物体面前，我们如何感知自我运动？相反，我们在自我运动时如何感知物体的运动？许多研究都集中在这两个相关但相反的问题中的一个上，但很少有研究将它们放在一起研究。研究表明，尽管观察者可以清楚地感知并将物体运动与自运动（即光流）引起的环境全局图像运动分离开来，但对自运动方向（即航向）的感知仍然会受到独立运动物体的影响。同样，也有报道称，识别场景相关物体运动的能力不受感知头部能力的限制或束缚。这表明这两个过程可能发生在光流处理的不同层次，但到目前为止，还没有研究系统地检验这种可能性，也没有计算模型可以捕捉到观察到的现象。在目前提出的研究中，我们计划解决这些问题。首先，我们将研究在什么条件下观察者将移动物体从头部感知中分离出来。其次，我们将研究观察者如何从光流/静态世界中分离运动对象。第三，我们将研究在什么条件下观察者将多个移动物体组合成一个连贯的整体，并将其从头部感知中分离出来。第四，我们将研究观察者如何从光流/静态世界中分离多个运动物体。最后，使用虚拟现实设置，我们将研究非视觉信息在独立运动物体存在时对头部的感知以及在自我运动期间对运动物体的感知中所起的作用。我们将对性能数据进行计算建模，以全面了解大脑如何将多模态感官线索结合起来，在运动物体存在时感知自我运动，以及在自我运动期间感知物体运动。当前项目的发现可以为负责不同水平光流处理的潜在神经机制模型的架构提供信息。

How do we perceive self-motion in the presence of independently moving objects? Conversely, how do we perceive object motion during self-motion? Much research has centered on one of these two related but opposing questions but very few studies have examined them together. It has been shown that the perception of the direction of self-motion (i.e., heading) can still be affected by an independently moving object even though observers can clearly perceive and segregate the object motion from the global image motion of the environment caused by self-motion (i.e., optic flow). Similarly, it has also been reported that the ability to identify scene-relative object movement is not limited by, or yoked to, the ability to perceive heading. This suggests that these two processes might happen at different levels of optic flow processing, but so far, no study has systematically examined this possibility and no computation modeling can capture the observed phenomena. In the current proposed research, we plan to address these questions. First, we will examine under what conditions observers segregate a moving object from the perception of heading. Second, we will examine how observers segregate a moving object from the optic flow/static world. Third, we will examine under what conditions observers combine multiple moving objects into a coherent ensemble and segregate it from the perception of heading. Fourth, we will examine how observers segregate multiple moving objects from the optic flow/static world. Last, using a virtual reality setup, we will examine the roles that non-visual information play in the perception of heading in the presence of independent moving objects and the perception of moving object during self-motion. We will computationally model the performance data to develop a comprehensive understanding of how the brain combines multimodal sensory cues for the perception of self-motion in the presence of moving objects and the perception of object motion during self-motion. The findings from the current project can inform the architecture of a model of the underlying neural mechanism responsible for different levels of optic flow processing.