Too many trees to see the forest: Performance, event-related potential, and functional magnetic resonance imaging manifestations of integrative congenital prosopagnosia
Too many trees to see the forest: Performance, event-related potential, and functional magnetic resonance imaging manifestations of integrative congenital prosopagnosia
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DOI：
10.1162/jocn.2007.19.1.132
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发表时间：
2007-01-01
影响因子：
3.2
通讯作者：
Robertson, Lynn C.
中科院分区：
文献类型：
--
作者：
Bentin, Shlomo;DeGutis, Joseph M.;Robertson, Lynn C.
结合神经心理学、事件相关电位（ERP）和功能性磁共振成像（fMRI）方法，对K.W.，先天性面容失认症我们证明，K.W.的视觉感知的特征是几乎前所未有的无法识别面部，对局部特征的大偏差，以及不限于面部的全局/视觉处理的极端缺陷。这种模式可以适当地标记为先天性整合性面孔失认症，并解释了一些，尽管不是全部，面部识别障碍的情况下，没有可识别的大脑病变。面部选择性的缺失在面部处理的生物标记物fMRI（梭形面部区域[FFA]）和ERPs（N170）中都是明显的。然而，这两种神经信号可能表现出不同的感知机制。而N170是由发生在视野中的容貌刺激触发的，在尾侧脑中的面部选择性功能磁共振成像激活不足与全球处理缺陷的严重程度相关。这种相关性表明，FFA可能与全球/神经计算，人脸识别的一个重要组成部分。
Neuropsychological, event-related potential (ERP), and functional magnetic resonance imaging (fMRI) methods were combined to provide a comprehensive description of performance and neurobiological profiles for K.W., a case of congenital prosopagnosia. We demonstrate that K.W.'s visual perception is characterized by almost unprecedented inability to identify faces, a large bias toward local features, and an extreme deficit in global/configural processing that is not confined to faces. This pattern could be appropriately labeled congenital integrative prosopagnosia, and accounts for some, albeit not all, cases of face recognition impairments without identifiable brain lesions. Absence of face selectivity is evident in both biological markers of face Processing, fMRI (the fusiform face area [FFA]), and ERPs (N170). Nevertheless, these two neural signatures probably manifest different perceptual mechanisms. Whereas the N170 is triggered by the occurrence of physiognomic stimuli in the visual field, the deficient face-selective fMRI activation in the caudal brain correlates with the severity of global processing deficits. This correlation suggests that the FFA might be associated with global/configural computation, a crucial part of face identification.