How does visual long-term memory implement control over visual attention?

在我们的日常生活中，我们经常应用我们的先验知识，同时与自然世界的所有复杂性进行互动。考虑一次去杂货店的简单旅行。首先，你可能要在一张凌乱的桌子上找到你的车钥匙。你的办公桌上可能有一些东西，比如假日照片、削铅笔刀或电脑，这些东西自然会引起注意，但在去商店时却没有用，所以必须忽略它们。然后，找到钥匙并开始驾驶，必须忘记钥匙，而是记住照顾玩耍的孩子，行人，骑自行车的人，其他司机，交通信号灯，街道标志和地标，以安全地沿着正确的路线前往商店。尽管在这个看似简单的任务中存在所有明显的挑战，但人们可以轻松地完成它，以及更复杂的任务。该项目旨在更好地了解先验知识如何指导我们当前的行动和对环境的看法。更好地处理这个过程可以帮助我们理解人类能力的一个基本要素，即使是我们最先进的人工智能系统也仍然无法实现。这项研究对社会的一个实质性好处是：有可能了解并改善驾驶员或空中交通管制员的注意力控制。除了在心理学和神经科学方面产生更广泛的影响外，科学家们还将参与公共宣传活动，如年度Brain Blast活动，Brain Bios播客和K-12教师-神经科学家合作伙伴关系，以提高对神经科学的理解和欣赏。为了了解先前的知识如何指导感知和当前的行为，该建议涉及非侵入性地记录来自在杂乱场景中搜索特定对象的人的脑电活动（利用脑电图或EEG）。这些场景是计算机屏幕上随机排列的物体的图片。研究人员将使用这些记录来研究是否需要有意识地记住先验知识（视觉长期记忆中的模板）来指导视觉注意力和视觉空间行为，如视觉目标检测。使用这种方法，研究人员可以测量大脑活动，跟踪你存储在记忆中的内容，以及你在场景中关注的内容。对这些数据的分析将揭示与物体记忆相关的大脑活动是否是你所需要关注的那个物体。这些实验要解决的一个关键问题是长时客体记忆和短时工作记忆对注意客体搜索的相对贡献。将使用EEG结合无创经颅脑刺激来测试竞争假设。科学家们还将研究，如果你以前在一个场景中发现了一个物体，那么它在未来是否会变得特别难以忽视。假设是，先前搜索过的对象将导致在未来的搜索中更多的注意力被吸引到该对象。实验将测试这种效应是否可以在大脑的反应中观察到。初步结果表明，记忆塑造了对特定对象的注意力，此外，人们可以同时在记忆中保存多个对象，并使用这些搜索模板同时寻找多个对象，这是人工智能系统目前不可能实现的壮举。这些发现将通过测试人类注意力和记忆力的模型来推动科学进步，并帮助我们设计更好的人工智能系统，使其能够与人类能力相匹配，并可能与人类更好地合作。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

In our everyday lives we often apply our prior knowledge while simultaneously interacting with the natural world in all its complexity. Consider a simple trip to the grocery store. First, one might have to find your car keys on a messy desk. Your desk may have items like a holiday photo, pencil sharpener or a computer that naturally draw attention but are of no use in going to the store, so they must be ignored. Then, having found the keys and starting to drive, one must forget the keys and instead remember to attend to children at play, pedestrians, cyclists, other drivers, traffic signals, street signs and landmarks to safely follow the right route to the store. Despite all the challenges apparent in even this seemingly simple task, people accomplish it, and far more complex tasks, with apparent ease. This project seeks to gain a better understanding of how prior knowledge guides our current actions and perceptions of the environment. A better handle on this process can help us understand a fundamental element of human ability that still eludes even our most advanced artificial intelligence systems. A substantial benefit to society is inherent in the research: the potential to understand and thereby improve attentional control for drivers or air traffic controllers. In addition to the broader impact in psychology and neuroscience, scientists will engage in public outreach such as the Annual Brain Blast events, the Brain Bios podcast, and the K-12 Teacher-Neuroscientist partnership to improve understanding and appreciation of neuroscience.To understand how prior knowledge guides perception and current behavior, this proposal involves non-invasively recording electrical brain activity (with electroencephalography or EEG) from people searching for particular objects in cluttered scenes. These scenes are picture of objects arranged randomly on a computer screen. The researchers will use these recordings to investigate whether prior knowledge (templates in visual long-term memory) needs to be intentionally held in mind to guide visual attention and visuospatial behavior such as visual target detection. Using this approach, researchers can measure brain activity that tracks what you store in memory, as well as what you pay attention to in the scenes. Analysis of these data will reveal whether brain activity related to object memory is all you need to pay attention to that object. A key question these experiments will resolve is the relative contribution of long-term object memory and short-term working memory to attentional object search. Competing hypotheses will be tested using EEG combined with noninvasive transcranial brain stimulation. Scientists will also study whether if you have previously found an object in a scene whether it then becomes particularly difficult to ignore in the future. The hypothesis is that previously having searched for an object will lead to more attention being drawn to that object in a future search. Experiments will test whether this effect can be observed in the response of the brain. Preliminary results suggest that memory shapes attention for specific objects and moreover, that people can simultaneously hold multiple objects in memory, and use these search templates to look for multiple objects at the same time, a feat that is currently impossible for artificial intelligence systems. These findings will be used to make scientific progress by testing models of human attention and memory, as well as helping us design better artificial intelligence systems that can match human ability and potentially better partner with humans as well.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.