Multiple Object Awareness

世界是一个充满活力的地方。物体移动，信息变化，人类观察者需要不断更新他们对那个世界的表示，以便继续有效地发挥作用。很明显，人类缺乏持续监测一切的能力，但限度是什么？在经典的实验中，当人们在屏幕上移动时，他们必须跟踪项目的子集，如果显示的所有项目都相同，他们似乎可以跟踪3-4个项目，如果项目不同，他们似乎只能跟踪2-3个项目，而且他们还必须跟踪项目的身份。然而，这些数字似乎被人为地降低了，我们个人的经验是，我们的视觉感知要大得多。关键原因似乎是，传统的实验设计没有考虑到对物品身份和位置的部分了解。我们开发了多对象感知(MOA)任务来测量这种部分知识。当我们包含部分知识时，事实证明你对8-12个项目有所了解，而不仅仅是2-4个项目。我们为什么要关心这个？许多现实世界的任务包括能够在不断变化的世界中快速找到多个项目并与其交互。想象一个指挥官，试图跟踪他的小队和他的敌人，同时监控他周围的其他行动或第一反应人员，处理不断变化的事故现场。了解MOA的能力可以影响工作场所(例如飞机驾驶舱)的设计。此外，培训可能会提高MOA的能力。如果事实证明是这样，那么MOA可以提供一条改进任务的途径，从监控手术室中的多个信息流到关注你的三年级班级。本项目中使用的基本MOA任务是对多对象跟踪(MOT)和多身份跟踪(MIT)任务的修改。观察者监视一组移动的对象(我们试点工作中的卡通动物)。观察员被要求尽其所能跟踪所有物体。每隔一段时间，我们就会用圆盘盖住所有物品，询问特定动物的位置。关键的创新是，我们要求观察者不断点击磁盘，直到他们找到目标动物。作为一个观察者，如果你是在猜测，你需要平均点击一半的项目。如果您对目标位置有所了解，则需要的点击次数会更少。根据所需的点击次数，可以得出MOA的容量估计为8-12个项目，远远大于MOT或MIT。我们的具体计划是：(1)筛选大量人群，以测试MOA将显示出比MOT或工作记忆更广泛的自然变化范围的假设，(2)测试MOA是可训练的假设，而MOT和工作记忆是不可训练的，以及(3)在更复杂、更现实的环境中研究MOA。整合组织系统部门的行为系统集群参与了该奖项的共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The world is a dynamic place. Objects move, information changes, and human observers need to keep updating their representations of that world in order to continue to function effectively. It is obvious that humans lack the capacity to monitor everything continuously but what is the limit? In classic experiments where people have to track subsets of items as they move around a screen, they seem to be able track 3-4 if all items in the display are identical, and just 2-3 if the items are distinct and they also have to track the identities of the items. However, these numbers seem artificially low, and our personal experience is that our visual awareness is much larger. The key reason seems to be that traditional experimental designs do not account for partial knowledge of items' identity and location. We developed the Multiple Object Awareness (MOA) task to measure this partial knowledge. When we include partial knowledge, it turns out that you know something about 8-12 items, not just 2-4. Why do we care? Many real-world tasks involve being able to rapidly find and interact with multiple items in a changing world. Think of a commander, trying to keep track of his squad and his enemies while monitoring the rest of the action around him or first responders, handling an evolving accident scene. Understanding MOA capacity can impact the design of workplaces (e.g. aircraft cockpits). Moreover, training may improve MOA capacity. If this proves to be the case, then MOA could provide a path to improvement on tasks from monitoring multiple streams of information in an operating room to keeping any eye on your 3rd grade class. The basic MOA tasks, used in this project, are modifications of the Multiple Object Tracking (MOT) and Multiple Identity Tracking (MIT) tasks. Observers monitor a set of moving objects (cartoon animals in our pilot work). The observers are asked to keep track of all of the objects as best they can. Every so often, we cover all items with disks and ask about the location of a specific animal. The crucial innovation is that we ask observers to keep clicking on disks until they find the target animal. As an observer, if you are guessing, you need to click on half the items on average. If you have some idea about the target location, you will need fewer clicks. Based on the number of clicks required, it is possible to derive a MOA capacity estimate of 8-12 items, far greater than MOT or MIT. Our specific plans are: (1) To screen a large population in order to test the hypothesis that MOA will show a wider natural range of variation than MOT or working memory, (2) to test the hypothesis that MOA is trainable in ways that MOT and working memory are not, and (3) to study MOA in more complex, realistic settings.The Behavioral Systems Cluster in the Division of Integrative Organismal Systems participated in co-funding of the award.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.