Face Impressions: Neuroscience & VR Training and Research

面部印象：神经科学

• 批准号: 7489518
• 负责人: LESLIE A. ZEBROWITZ
• 金额: $ 12.51万
• 依托单位: BRANDEIS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7489518
• 关键词: Appearance; Arts; Autistic Disorder; Award; Behavioral; Brain; Categories; Computer Simulation; Computer software; Consensus; Disease; Emotions; Environment; Equipment; Face; Face Processing; Facility Construction Funding Category; Foundations; Functional Magnetic Resonance Imaging; Funding; Future; Grant; Human; Imaging Techniques; Individual; Intervention; Knowledge; Learning; Link; Magnetic Resonance Imaging; Mental disorders; Methods; Neural Network Simulation; Neurosciences; Pattern; Property; Range; Rate; Reaction; Research; Research Training; Scientist; Social Environment; Social Interaction; Social Perception; Social Psychology; Structure; System; Techniques; Testing; Training; Universities; Work; base; computer science; fitness; impression; laboratory facility; member; neural model; novel; prototype; psychologic; relating to nervous system; research study; response; social; trait; virtual; virtual reality

DESCRIPTION (provided by applicant): Facial appearance strongly influences first impressions, which show remarkable consensus and yield significant social consequences. The long-range objective is to explain consensual impressions among normal individuals and their absence in individuals with disorders such as autism. It is hypothesized that qualities that are accurately revealed by facial features that mark babies, unfitness, or identity are overgeneralized to people whose facial structure resembles that of babies, a particular level of fitness, or a particular identity. Four specific research aims are: 1)connectionist modeling tests the facial identity overgeneralization hypothesis (FIOH) that the tendency for responses to strangers to vary with their facial resemblance to known individuals contributes to social categorization effects; 2)functional Magnetic Resonance Imaging (fMRI) investigates brain activation patterns in response to faces that are predicted from each of the overgeneralization hypotheses; 3)generalized mere exposure paradigms investigate whether familiarization with the facial prototype of a category changes impressions of new category members, as predicted by the FIOH; 4)virtual reality methods test face overgeneralization hypotheses through behavioral responses to faces in various social contexts. Four training aims are: 1) increased knowledge of the conceptual foundations of computer modeling of neural systems and the computer software used to implement neural network simulations; 2) increased knowledge of brain structure and function and fMRI techniques; 3) learning to use virtual environments to assess the perceived behavioral affordances of different facial qualities; 4) integrating various methods to provide more sophisticated tests of the face overgeneralization hypotheses. The research and training benefit from excellent laboratory facilities, state of the art equipment, and interactions with outstanding scientists at Brandeis University and the MGH-NMR Center. Integrating social psychology, computer science, and neuroscience promises to advance the understanding of social perception. The focus on facial information offers a novel theoretical perspective, demonstrating that intrinsic properties of faces contribute to social biases that have been largely viewed as social constructions. It also provides a foundation for research that may elucidate neural bases of social deficits, as in autism, and develop intervention techniques to modify reactions to faces.

描述（由申请人提供）：面部外观强烈影响第一印象，这表现出显着的共识并产生重大的社会后果。长期目标是解释正常人之间的共识印象以及患有自闭症等疾病的人所缺乏的共识印象。据推测，通过标记婴儿、不健康或身份的面部特征准确揭示的品质被过度概括为面部结构类似于婴儿、特定健康水平或特定身份的人。四个具体的研究目标是：1）联结主义模型测试面部身份过度概括假设（FIOH），即对陌生人的反应倾向因其与已知个体的面部相似性而变化，从而导致社会分类效应； 2）功能磁共振成像（fMRI）研究根据每个过度概括假设预测的面部反应的大脑激活模式； 3）广义纯粹暴露范式研究熟悉某个类别的面部原型是否会改变新类别成员的印象，正如 FIOH 所预测的那样； 4）虚拟现实方法通过在各种社会背景下对面孔的行为反应来测试面孔过度概括假设。四个培训目标是：1）增加对神经系统计算机建模和用于实现神经网络模拟的计算机软件的概念基础的了解； 2）增加对大脑结构和功能以及功能磁共振成像技术的了解； 3）学习使用虚拟环境来评估不同面部品质的感知行为可供性； 4）整合各种方法，为面对过度概括假设提供更复杂的测试。研究和培训受益于优秀的实验室设施、最先进的设备以及与布兰代斯大学和 MGH-NMR 中心的杰出科学家的互动。社会心理学、计算机科学和神经科学的结合有望促进对社会感知的理解。对面部信息的关注提供了一个新颖的理论视角，证明面部的内在属性会导致社会偏见，而这些偏见在很大程度上被视为社会建构。它还为研究奠定了基础，可以阐明社交缺陷（如自闭症）的神经基础，并开发干预技术来改变对面孔的反应。