Testing and building models of face perception via acquired prosopagnosia

面部信息处理是社会互动的核心。我们用脸来识别人，确定他们的感受，他们在关注什么，基于脸的特征判断有助于我们如何对待他人(例如，这个人值得信赖吗？对我有吸引力？)在人脑中，人脸识别是由包括视觉区、边缘区和前额叶区在内的分布式皮质网络介导的。然而，人脸处理的计算性质和不同区域对人脸处理的作用仍然不清楚。为了更好地理解人脸处理的计算和神经基础，我们将对那些大脑受损、无法识别人脸的参与者进行行为和神经成像研究。这种情况被称为获得性面孔失认症，我们的实验室已经开发了世界上最大的获得性面孔失认症参与者数据库（N=20并且正在增长）。这些面孔失认的参与者有不同程度的面部感知障碍以及不同程度的面部处理网络损伤。这个项目将提高我们对正常面部处理个体的面部处理的认识，也将是开发获得性面孔失认症分类系统的第一步。这样的分类系统将是有价值的，因为不同类型的面孔失认症可能对不同类型的干预有反应。当前提议的主要目的是测试两个有影响力的面部模型的基本认知和神经预测。先前的研究调查了面孔失认症患者的面部感知能力，只在小样本中检查了一些能力。相比之下，该计划将调查至少20名患者的面部感知能力，这些患者来自PI的面孔失认症数据库（http://www.faceblind.org）。这些研究将涉及三个主要目标。他们将测试并在必要时修改一个广泛的面部感知模型的认知结构（目标1），测试和修改一个面部特征感知模型（目标2），并测试这两个模型的神经预测（目标3）。该计划将产生两个主要的智力成果：对面部感知模型的评估及其必要的修订，以及获得性面孔失认症的分类。创建获得性面孔失认症的分类将是一个重大的进步，因为目前将不同类型的获得性面孔失认症分组的做法阻碍了对病情的理解和开发康复方法的努力。媒体对我们研究结果的报道可能会提高公众对面孔失认症的认识。所创建的面部感知电池将作为用户友好的程序免费提供，对研究人员和临床医生都很有用。本科研究人员，其中许多人是科学界代表性不足的少数民族成员，将在这个项目中获得实践经验。

Face processing is central to social interaction. We use faces to identify people, determine what they are feeling, what they are attending to, and trait judgments based on faces contribute to how we behave toward others (e.g., Is this person trustworthy? Attractive to me?). In the human brain, face recognition is mediated by a distributed cortical network that includes visual, limbic, and prefrontal areas. However, the nature of the computations underlying face processing and the function of the different areas contributing to face processing remain unclear. To better understand the computational and neural basis of face processing, we will carry out behavioral and neuroimaging studies with participants who have suffered brain damage that disrupts their ability to recognize faces. This condition is known as acquired prosopagnosia, and our lab has developed the world's largest database of participants with acquired prosopagnosia (N=20 and growing). These prosopagnosic participants have varied face perception impairments as well as varied damage to the face processing network. This project will advance our knowledge of face processing in individuals with normal face processing and will also be the first step toward the development of a classification system for acquired prosopagnosia. Such a classification system would be valuable, because different types of prosopagnosia are likely to be responsive to different types of interventions. The primary objective of the current proposal is to test fundamental cognitive and neural predictions of two influential models of face. Previous studies investigating face perception in prosopagnosia have examined only a few abilities in small samples. The proposed project, in contrast, will investigate a wide range of face perception abilities in at least 20 patients drawn from the PI's prosopagnosia database (http://www.faceblind.org). The studies will address three primary aims. They will test and, if necessary, revise the cognitive structure of a broad model of face perception (Aim 1), test and revise a model of facial trait perception (Aim 2), and test the neural predictions of these two models (Aim 3). The proposed project will yield two main intellectual outcomes: evaluation of the face perception models and their revision as necessary, and a taxonomy of acquired prosopagnosia. Creation of a taxonomy of acquired prosopagnosia will be a major advance, because the current practice of grouping together different types of acquired prosopagnosia hampers efforts to understand the condition and develop rehabilitation methods. Media coverage of our findings is likely to increase public awareness of prosopagnosia. The face perception battery created will be made freely available as user-friendly programs that will be useful for both researchers and clinicians. Undergraduate researchers, many of whom are members of minorities under-represented in science, will get hands-on experience in this project.