The speed of holistic face processing

整体人脸处理速度

• 批准号: RGPIN-2019-06849
• 负责人: Tanaka, James
• 金额: $ 3.42万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=764157
• 关键词: speed; holistic; face; processing

The face of a familiar friend or colleague is recognized instantaneously without conscious effort or forethought. Although face recognition occurs quickly, little is known about the exact timing and the underlying cognitive operations and brain mechanisms that mediate fast recognition. My proposed research will introduce a novel and powerful technique to test the "how" and "when" of face recognition. We assume that rapid face recognition requires holistic processing in which a face is recognized as a whole face stimulus rather than recognition of its individual parts. An untested question in the face recognition literature is the speed at which holistic face processing occurs. In a preliminary test of rapid holistic processing (RHP) I conducted with a postdoctoral trainee, a face was flashed on the screen for 17 to 500 ms, followed by a white-noise mask. The key finding was that the eyes were better recognized in the whole face than in isolation when presented for the shortest duration of 17ms (Tanaka & Xu, 2018). Although our results suggest that holistic face recognition occurs very quickly, more stringent psychophysical tests of rapid face recognition are warranted to identify the threshold of RHP; that is, the precise exposure duration at which the whole face advantage emerges. Over the next five years, my research group will first assess the RHP threshold across converging psychophysical paradigms with an ultra-high speed 240 Hz display monitor, capable of presentation rates of 4 ms. After determining the RHP threshold, we will move on to examine the generalizability and limits of RHP. We will attempt to disrupt RHP for faces by inverting the face stimulus or scrambling its internal features. We will also test whether RHP extends to the perception of facial emotion and non-face objects (i.e., houses). Building on these experiments, we will examine the effects of perceptual experience and learning by investigating the RHP across the lifespan and in real-world and laboratory-trained experts. In related work, we will isolate the brain dynamics of rapid holistic recognition of face identity and emotion by using a frequency tagging method in electroencephalography (EEG) where individual face parts (eye, nose, mouth) will be shown at different frequency rates. By focusing on the temporal dynamics of holistic processing, our research will open up exciting, and as yet, unexplored avenues of research in face and object recognition. The experiments will yield important conceptual insights that will deepen our understanding of cognitive and neural-based theories involving the speed of face recognition. The work will significantly advance the field and lead to new measures for assessing face recognition in healthy adults and in people who experience deficits in their face recognition abilities, such as individuals with autism, schizophrenia and dementia.

熟悉的朋友或同事的面孔在没有有意识的努力或预先考虑的情况下立即被识别出来。虽然人脸识别发生得很快，但人们对准确的时间和潜在的认知操作以及介导快速识别的大脑机制知之甚少。我提出的研究将引入一种新颖而强大的技术来测试人脸识别的“如何”和“何时”。我们假设，快速人脸识别需要整体的处理，其中一张脸被认为是一个整体的脸刺激，而不是识别其个别部分。人脸识别文献中一个未经测试的问题是整体人脸处理发生的速度。在我与一名博士后实习生进行的快速整体处理（RHP）的初步测试中，一张脸在屏幕上闪烁了17到500毫秒，然后是白噪声面具。关键的发现是，在17毫秒的最短持续时间内，整个面部的眼睛比单独的眼睛更容易识别（Tanaka & Xu，2018）。 虽然我们的研究结果表明，整体的人脸识别发生得非常快，更严格的心理物理测试快速人脸识别是必要的，以确定阈值的RHP，也就是说，精确的曝光时间在整个脸的优势出现。在接下来的五年里，我的研究小组将首先评估跨融合心理物理学范式的RHP阈值与超高速240 Hz显示监视器，能够呈现率为4 ms。确定RHP阈值后，我们将继续研究RHP的普遍性和局限性。我们将尝试通过反转面部刺激或扰乱其内部特征来破坏面部的RHP。我们还将测试RHP是否扩展到面部情感和非面部对象的感知（即，房屋）。在这些实验的基础上，我们将通过调查整个生命周期以及现实世界和实验室培训专家的RHP来研究感知经验和学习的影响。在相关的工作中，我们将使用脑电图（EEG）中的频率标记方法来分离快速整体识别面部身份和情绪的大脑动力学，其中各个面部部位（眼睛，鼻子，嘴巴）将以不同的频率显示。 通过关注整体处理的时间动态，我们的研究将开辟令人兴奋的，迄今为止，在面部和物体识别的研究未探索的途径。这些实验将产生重要的概念性见解，加深我们对涉及人脸识别速度的认知和神经理论的理解。这项工作将大大推进该领域的发展，并为评估健康成年人和面部识别能力不足的人（如自闭症、精神分裂症和痴呆症患者）的面部识别提供新的措施。