Collaborative Research: Control and Adaptation of Attentional Processing: Empirical and Computational Investigations

人类的视觉非常灵活。 考虑在人群中寻找熟悉的面孔，在杂乱的厨房里找到车钥匙，在足球场上追逐对手，或者穿过拥挤的餐馆找到一张桌子。 视觉是如何适应如此多样的视觉环境并实现如此多样化的目标的？ 其中一个关键是选择性注意力，它允许一个人专注于视觉环境的相关方面。 但是大脑如何决定什么是相关的呢？ 视觉注意力控制的本质是什么？在美国国家科学基金会的支持下，Shaun Vecera博士和Michael Mozer博士提出了研究选择性注意的研究。 Vecera博士将进行实验研究，探索人类在新任务和陌生环境中的行为，以研究人们如何利用环境中的视觉线索来提高表现。 Mozer博士将建立计算机模拟模型来解释实验结果。 这项研究的更广泛的影响包括构建具有人类视觉灵活性的人工系统，以及改进计算机系统和机械或电子设备的用户界面设计。 此外，拟议的研究可能会为脑损伤导致的控制缺陷的诊断提供信息。 人类控制的计算机模型可以以各种方式受损，以模拟脑损伤，从而更好地了解后果和补救策略。

Human vision is exceptionally flexible. Consider searching for a familiar face in a crowd, finding car keys in a cluttered kitchen, chasing down an opponent in football, or threading through a crowded restaurant to find a table. How does vision accommodate such a variety of visual environments and achieve such diverse goals? One key is selective attention, which allows a person to focus on relevant aspects of the visual environment. But how does the mind determine what is relevant? What is the nature of control of visual attention?With support from the National Science Foundation, Dr. Shaun Vecera and Dr. Michael Mozer propose research to investigate selective attention. Dr. Vecera will conduct experimental studies that explore human behavior in novel tasks and unfamiliar environments to investigate how people exploit visual cues in the environment to enhance performance. Dr. Mozer will build computer simulation models to explain the experimental results. Broader impacts of this research include building artificial systems with the flexibility of human vision and improving the design of user interfaces for computer systems and mechanical or electronic devices. Additionally the proposed research may inform the diagnosis of control deficits due to brain damage. A computer model of human control can be damaged in various ways, to simulate brain damage, leading to a better understanding of the consequences and strategies for remediation.