Components, Correlates and Mechanisms of Object Recognition

视觉决策在各种职业中发挥着至关重要的作用，影响着每天无数次做出这些决策的专家。该项目旨在了解人们如何以及为什么改变他们做出视觉决定的能力。通过分析大量参与者在多个任务中的表现，该项目试图揭示视觉能力的不同方面，特别是与感知和记忆有关的方面。它将一般的物体识别能力与心理学家常规测量的其他能力进行了比较，并探讨了视觉能力如何帮助预测个人成为感知专家的潜力。额外的活动吸引高中生，教他们在能力倾向测试中使用较少文化偏见的能力的好处。这些发现有可能影响依赖视觉决策的职业，如法医和医学成像，促进测试的包容性，推进视觉认知的研究。采用多变量和潜在变量方法，其中每个结构都由几个任务来衡量，该项目探索了支持对象识别的能力结构。它探讨了它们与既定能力的关系，它们如何预测专业知识的获得，以及这些个体差异背后的机制。该项目开发了一系列具有良好心理测量特性的任务，用于研究物体识别，测试感知和记忆成分之间的区别。这项工作评估了物体识别能力相对于现有能力的增量预测能力，在预测通过多阶段学习获得的专业知识方面，既有一般能力（如智能），也有感性能力（如空间处理）。在卫星图像中检测绿色气体排放和皮肤科培训方面与专家合作，为评估这些措施的预测有效性提供了实际情况。该项目还通过研究探索视觉能力和针对众所周知的日益复杂的机制的操作之间的相互作用来研究三种机制：感知分化，统计学习和维度学习。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Visual decisions play a crucial role in various occupations, impacting experts who make these decisions countless times each day. The project aims to understand how and why people vary their ability to make visual decisions. By analyzing the performance of large groups of participants across multiple tasks, the project seeks to uncover different aspects of visual abilities, particularly in relation to perception and memory. It compares general object recognition with other abilities routinely measured by psychologists and explores how visual abilities can help predict an individual's potential to become a perceptual expert. Additional activities engage high school students and teach them about the benefits of using less culturally-biased abilities for aptitude testing. The findings hold the potential to impact occupations reliant on visual decision-making, such as forensics and medical imaging, fostering inclusivity in testing and advancing research in visual cognition.Employing a multivariate and latent variables approach, in which each construct is measured by several tasks, the project explores the structure of abilities that support object recognition. It explores how they relate to established abilities, how they predict the acquisition of expertise, and what mechanisms underlie these individual differences. The project develops a broad range of tasks with good psychometric properties for the study of object recognition, testing for a distinction between perceptual and mnemonic components. The work assesses the incremental predictive power of object recognition abilities over existing abilities, both general (like intelligence) and perceptual (like spatial processing) in the prediction of expertise acquired through multi-session learning. Collaborations with experts in detecting green gas emissions in satellite images and in dermatology training provide real-world situations in which to assess the predictive validity of the measures. The project also investigates three mechanisms through studies that explore the interaction between visual abilities and manipulations targeting well-known mechanisms of increasing complexity: Perceptual Differentiation, Statistical Learning, and Dimensional Learning.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.