Modeling Face Perception

面部感知建模

• 批准号: 7121512
• 负责人: GARRISON W COTTRELL
• 金额: $ 27.93万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-08-01 至 2008-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7121512
• 关键词: behavior test; clinical research; computational neuroscience; culture; emotions; eye movements; face expression; human subject; learning; model design /development; neural information processing; neuropsychology; perception; performance; psychological models; saccades

DESCRIPTION (provided by applicant): There has been a great deal of progress in understanding how complex visual objects, in particular, human faces, are processed by the cortex. At the same time, sophisticated neural network models have been developed that do many of the same tasks required by these cortical areas. The aim of this proposal is to extend these simplifying models toward an understanding of the extent to which facial expression processing is "universal," versus the extent to which it is experientially mediated. In particular, we focus upon elucidating the following issues through modeling: (1) Understanding cultural variation in expression recognition: contrasting the influence of other race effects versus cultural display rules; (2) Understanding how we become face "experts." Why does the same region of the Fusiform Gyrus get recruited for faces as well as other visual tasks we may be expert in? (3) Understanding the dynamics of facial expertise: How are eye movements planned for efficient feature extraction? In each case, we have developed or will develop a neurocomputational model of the process. Cultural and other-race experience will be modeled by the composition of the internal representations and the training signals of our model. Facial expertise is modeled as a combination of different task requirements (varying the level of categorization required) and length of training. Eye movement modeling will be based on novel and traditional methods for extracting the informative locations on the face for each task. We will develop a theoretical criterion for saccade targets the face based upon mutual information between feature values and the categories required for the task. We also will be performing behavioral experiments to test the predictions of our model. The project will shed light on the way faces are represented and processed by the brain, and should give insights into the problems underlying deficits in face processing such as prosopagnosia.

描述（由申请人提供）：在理解皮质的复杂视觉对象（尤其是人体面孔）如何处理中，已经取得了很大进展。同时，已经开发出复杂的神经网络模型，这些模型执行了这些皮质区域所需的许多相同任务。该提案的目的是将这些简化的模型扩展到对面部表达处理“通用”与经验介导的程度的程度的理解。特别是，我们专注于通过建模来阐明以下问题：（1）理解表达识别的文化变化：将其他种族影响与文化展示规则的影响对比； （2）了解我们如何成为“专家”。为什么我们可能从事的其他视觉任务会招募梭形回的同一区域？ （3）了解面部专业知识的动态：如何计划眼动作以进行有效的特征提取？在每种情况下，我们都开发或将开发该过程的神经计算模型。文化和其他种族经验将以内部表示形式的组成以及我们模型的训练信号进行建模。面部专业知识被建模为不同任务要求（改变所需的分类水平）和培训时间的组合。眼动建模将基于新颖和传统方法，用于为每个任务提取脸上的信息位置。我们将根据特征值和任务所需的类别之间的相互信息来制定扫视目标的理论标准。我们还将执行行为实验来测试我们的模型的预测。该项目将阐明面孔的代表和处理方式，并应深入了解诸如Prosopagnosia之类的面部处理中的缺陷问题。