Exploring mechanisms underlying face learning in infants and adults

面孔提供了关于其他人的丰富信息，包括他们的身份、性别、年龄、种族和情绪状态。感知这些信息的能力对于社会互动至关重要。成年人被认为是人脸“专家”--我们记住数以千计的单个人脸，我们使用专门的处理机制，这些机制适用于人脸，但不适用于其他视觉刺激，我们的神经系统与其他物体相比，优先调整为人脸。然而，在某些方面，我们可能不是面子专家。大多数脸部知觉研究都考察了使用严格控制的刺激区分两种身份的能力--例如，去掉头发的面孔照片，在统一背景下呈现的面孔，以及相同灯光下的面孔。在这些研究中，成年人看起来确实像专家。然而，当对人脸识别的研究更类似于成年人每天必须执行的任务时(例如，当你在杂货店看到你的新同事时，认出她)，成年人的表现就不像专家了。具体地说，当成年人看到自然变化的陌生面孔时--例如，在灯光、视点、面部表情、发型、背景背景等方面--他们很难确定两个不同的图像代表同一个人。然而，当我们必须识别熟悉的面孔时，我们就不会遇到同样的问题--我们能够识别我们在这种自然变异性中非常熟悉的人。提出这项研究的关键问题是：陌生面孔是如何变得熟悉的？也就是说，在遇到一张新面孔时，我们如何形成一个健壮而稳定的面孔表征，使我们能够跨自然变化识别这张面孔？这项拟议的研究将结合行为、眼球跟踪和电生理技术来解决成人和婴儿的这些问题。眼球跟踪将使我们能够确定婴儿和成年人在学习一张脸的过程中注意力模式是如何变化的，以及这些注意力模式如何预测我们能否很好地识别这张脸的新图像。EEG将使我们能够研究成人和婴儿对熟悉和陌生面孔的神经表征有何不同。本课题的研究将为我们理解人脸识别及其发展做出重要的理论贡献。它还将作出重要的实际贡献。在许多职业中，人脸识别--尤其是识别各种不同人脸的能力--至关重要(例如，边防官员必须确定身份证上的照片是否是站在他们面前的同一个人)。了解在现实世界条件下导致更好的人脸识别性能的因素可以为这些专业的培训提供信息。此外，拟议研究的结果可能为对表现出面部识别缺陷(例如自闭症谱系障碍)的发展中人群进行应用研究奠定基础。

Faces provide a wealth of information about other people, including their identity, gender, age, ethnicity, and emotional state. The ability to perceive this information is critical for social interactions. Adults are considered face "experts" - we remember thousands of individual faces, we use specialized processing mechanisms that apply to faces but not other visual stimuli, and we have neural systems that are preferentially tuned to faces compared to other objects. However, in some ways we may not be face experts. Most face perception studies examine the ability to distinguish between two identities, using tightly controlled stimuli - for example, pictures of faces where hair is removed, faces are presented against a uniform background, and lighting is the same. In these studies, adults do look like experts. However, when studies of face recognition are more similar to tasks that adults must perform everyday (e.g., recognizing your new colleague when you see her at the grocery store), adults do not perform like experts. Specifically, when adults see unfamiliar faces that vary naturally - e.g., in lighting, viewpoint, facial expression, hairstyle, background context - they have difficulty determining that two different images represent the same person. However, we do not have the same problem when we have to recognize familiar faces - we are able to recognize people we know well across this kind of natural variability. The key question motivating the proposed studies is: How do unfamiliar faces become familiar? That is, upon encountering a new face, how do we form a robust and stable representation of that face that allows us to recognize the face across natural variability? The proposed research will combine behavioural, eye-tracking, and electrophysiological techniques to address these questions in adults and infants. Eye-tracking will allow us to determine how infants' and adults' patterns of attention change as they are learning a face, and how those patterns of attention predict how well we are able to recognize novel images of that face. EEG will allow us to examine how neural representations of familiar and unfamiliar faces differ in both adults and infants. This program of research will make important theoretical contributions to our understanding of face recognition and its development. It will also make important practical contributions. There are numerous professions where face recognition - in particular, the ability to recognize faces across variability - is critical (e.g., border officials who have to determine if the picture on an ID card is the same person standing in front of them). Understanding the factors that lead to better face recognition performance under real-world conditions can inform training in these professions. Additionally, findings from the proposed studies may lay the foundation for applied research with developing populations who display face recognition deficits (e.g., autism spectrum disorders).