Visual feature perception during dynamic spatial attention and distraction

我们的视觉系统如何理解我们周围的世界？我们的大脑从最少的视觉输入中构建出令人难以置信的丰富的感知体验：眼睛视网膜上的光模式。一个主要的挑战是，环境提供的信息超过了我们的视觉系统一次完全处理的能力，所以我们依靠注意力机制来优先处理最相关的信息。注意力和知觉是重要的认知过程，影响着我们日常运作的方方面面。了解这些过程通常是如何运作的--以及我们何时容易受到知觉错误和扭曲的影响--对健康的视觉系统和各种疾病，以及从最大化人类行为到人工智能和技术开发的广泛应用都有重要影响。该项目的教育部分将为代表性不足的种族和民族群体增加STEM机会，加强本科教育，并提供社区外联服务。这份提案概述了一项为期三年的综合研究和教育计划，该计划旨在解决动态空间注意力和分心时视觉特征感知如何改变的问题。该提案调查了我们的视觉系统面临的一个根本挑战：我们如何成功地将关于一个物体是什么的信息与它在哪里的信息整合在一起？虽然绑定过程本身就具有足够的挑战性，但在动态视觉和认知过程中变得尤为关键，因为环境中往往有多个感兴趣的对象或位置，空间注意力不断转移。使用Pi Golomb最近开发的一个范式，我们检验了不稳定的空间注意会导致特征和物体知觉错误的假设。在目标1中，我们与注意力控制和分心方面的专家PiLeber合作，重点研究在分心条件下视觉特征知觉可能会如何改变。在目标2中，我们向一个更基本的方向展开，询问不同类型的动态空间注意可能如何影响多特征对象的对象整合。这些实验包括感知特征报告、概率混合建模、脑电阿尔法解码、眼球跟踪和基于奖励的操作的组合。这一创新和新颖的方法努力促进我们对如何实现稳定和综合的视觉感知的理解，特别是在动态注意力和分心的条件下。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。

How does our visual system make sense of the world around us? Our brains construct incredibly rich perceptual experiences from the rawest of visual inputs: patterns of light on the eye's retina. A major challenge is that the environment presents more information than our visual system can fully process at a time, so we rely on the mechanisms of attention to prioritize the most relevant information. Attention and perception are vital cognitive processes that affect every aspect of our daily functioning. Understanding how these processes typically work - and when we are susceptible to perceptual errors and distortions - has critical repercussions for both the healthy visual system and various disorders, along with broad-reaching applications ranging from maximizing human behavior to development of artificial intelligence and technology. The project's education component will increase STEM opportunities for underrepresented racial and ethnic groups, enhance undergraduate education, and offer community outreach. This proposal outlines a three-year integrated research and education plan addressing how visual feature perception is altered during dynamic spatial attention and distraction. The proposal investigates a fundamental challenge for our visual systems: How do we successfully integrate information about 'what' an object is with 'where' it is? While the binding process is challenging enough on its own, it becomes particularly crucial during dynamic vision and cognition, where there are often multiple objects or locations of interest in the environment and spatial attention is constantly shifting. Using a paradigm recently developed by PI Golomb, we test the hypothesis that unstable spatial attention can cause errors in feature and object perception. In Aim 1, we focus on how visual feature perception might be altered during conditions of distraction, in collaboration with co-PI Leber, an expert in attentional control and distraction. In Aim 2, we expand in an even more fundamental direction, asking how different types of dynamic spatial attention might impact object integration for multi-feature objects. The experiments include a combination of perceptual feature reports, probabilistic mixture modeling, EEG alpha decoding, eye-tracking, and reward-based manipulations. This innovative and novel approach strives to advance our understanding of how we achieve stable and integrated visual perception, especially under conditions of dynamic attention and distraction.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.