Face Perception: Mapping Psychological Spaces to Neural Responses

识别面孔的能力对于我们的社交世界至关重要。人类的视觉系统可以在一生中毫不费力地对数千张面孔进行分类、识别和记忆。使用功能性磁共振成像（fMRI）的研究已经确定了人类视觉皮层中的几个区域，这些区域对人脸有特异性和选择性的反应，但关于人脸识别的神经机制仍然存在关键问题。例如，目前尚不清楚面部选择区域是否对所有人脸都有同样的反应，或者面部相似性的感知测量与面部相似性的神经测量之间是如何关联的。在美国国家科学基金会的支持下，研究者将使用最新的方法创新，使高分辨率的功能磁共振成像，结合创新的心理物理学方法和计算模型来研究类别内面部表征的神经基础。该项目将确定驱动面部选择区域反应的基本属性，确定这些反应是否与个体一生中所经历的面部分布相一致，并确定神经反应的相似性是否与面部之间的感知或物理相似性密切相关。总的来说，这项研究将在理解神经反应如何支持我们识别个人面孔的能力方面提供重大进展。这项研究将具有重要的意义，不仅仅是为特定的面部表征计算理论提供支持。它将为比较任何其他视觉类别的表征提供一个有用的工具，例如，比较对面部和物体的神经反应，这是一个核心争论的问题。对正常面部识别的神经关联的理解也为理解面部识别障碍提供了重要的基础，这些障碍表现在生殖器官面孔失认症、阿斯伯格综合症和自闭症中，因此具有广泛的健康和社会意义。该项目还旨在通过进一步发展高分辨率功能磁共振成像技术，并通过研究不同的实验设计和高分辨率成像分析是否显示收敛的结果，来推进神经成像方法。最后，本研究将为本科生、研究生和博士后提供培训机会。

The ability to recognize faces is essential for navigating our social world. The human visual system can effortlessly categorize, identify, and remember thousands of faces over a lifetime. Research using functional magnetic resonance imaging (fMRI) has identified several regions in the human visual cortex that specifically and selectively respond to faces, but key questions remain with respect to the neural mechanisms underlying face recognition. For example, it is unclear whether face-selective regions are equally responsive to all human faces, or how perceptual measures of similarity correlate with neural measures of similarity between faces. With support from the National Science Foundation, the investigator will use recent methodological innovations that enable high-resolution fMRI, combined with innovative psychophysical methods and computational models to study the neural basis of within-category representation of faces. The project will identify the fundamental properties that drive responses in face-selective regions, determine whether these responses are tuned to the distribution of faces experienced by individuals over their lifetime, and determine whether measures of similarity of neural responses are tightly related to measures of perceptual or physical similarity among faces. Overall, this research will provide significant advancement in the understanding of how neural responses support our ability to identify individual faces. The research will have significant implications beyond providing support for a particular computational theory of face representation. It would provide a useful tool for comparing the representations of any other visual category, for example, comparing between neural responses to faces and to objects, which is an issue of central debate. The understanding of neural correlates of normal face identification also provides an important baseline for understanding impairments in face identification as manifested in cogenital prosopagnosia, Asperger's Syndrome and Autism, and as such has broad health and societal implications. This project also aims to advance neuroimaging methods by further developing high-resolution fMRI techniques and by examining whether different experimental designs and analyses for high-resolution imaging show convergent results. Finally, this research will provide training opportunities for students at the undergraduate, graduate, and post-doctoral levels.