MODELING FACE PERCEPTION

描述(申请人摘要)：已经取得了很大的进展 为了理解复杂的物体，特别是面部是如何被 人类。这项提议目的是扩展最近在计算方面的工作 情绪和面部处理的模型，以解释最近的数据 脑损伤患者和正常对照组的面孔加工。在所有的 这些研究的目的是了解人脸加工在多大程度上 通过建模和实验，被认为是“特殊的”。我们的特定 目标是：i)分析范畴知觉与认知之间的关系 我们的模型和人类受试者的情绪，通过平行的方式阐明 在模型和人体上使用相同的刺激进行实验；2)理解 此外，脸部、物体和表情的专门化“模块”可能会如何出现 通过竞争性学习机制和 先天偏见；3)了解各种“脑损伤”的影响 在我们的模型中，作为理解患者行为的一种途径。这些目标 将通过以数据为指导的仔细建模研究来解决。我们的 假设将通过构建神经网络模型来验证，该模型 与人类研究中使用的人脸图像相同。

DESCRIPTION (Applicant's abstract): There has been a great deal of progress in understanding how complex objects, in particular, faces, are processed by humans. The aim of this proposal is to extend recent work on computational models of emotion and face processing to account for recent data concerning face processing in brain-damaged patients and normal controls. In all of these studies, the goal is to understand to what extent face processing must be considered "special", through modeling and experiment. Our specific goals are to: I) analyze the relationship between categorical perception of emotion in our models and in human subjects as elucidated by parallel experiments on the models and humans using identical stimuli; 2) understand further how specialized "modules" may arise for face, object and expression recognition through combinations of competitive learning mechanisms and innate biases; 3) understand the effects of various kinds of 'brain damage" on our model, as a route to understanding patient behavior. These goals will be addressed through careful modeling studies guided by the data. Our hypotheses will be tested by constructing neural network models that process the same face images used in human studies.