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超越面部区域:面孔失认症的病灶网络图谱。

Looking beyond the face area: lesion network mapping of prosopagnosia.

机构信息

Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.

Berenson-Allen Center for Non-Invasive Brain Stimulation and Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

出版信息

Brain. 2019 Dec 1;142(12):3975-3990. doi: 10.1093/brain/awz332.

Abstract

Damage to the right fusiform face area can disrupt the ability to recognize faces, a classic example of how damage to a specialized brain region can disrupt a specialized brain function. However, similar symptoms can arise from damage to other brain regions, and face recognition is now thought to depend on a distributed brain network. The extent of this network and which regions are critical for facial recognition remains unclear. Here, we derive this network empirically based on lesion locations causing clinically significant impairments in facial recognition. Cases of acquired prosopagnosia were identified through a systematic literature search and lesion locations were mapped to a common brain atlas. The network of brain regions connected to each lesion location was identified using resting state functional connectivity from healthy participants (n = 1000), a technique termed lesion network mapping. Lesion networks were overlapped to identify connections common to lesions causing prosopagnosia. Reproducibility was assessed using split-half replication. Specificity was assessed through comparison with non-specific control lesions (n = 135) and with control lesions associated with symptoms other than prosopagnosia (n = 155). Finally, we tested whether our facial recognition network derived from clinically evident cases of prosopagnosia could predict subclinical facial agnosia in an independent lesion cohort (n = 31). Our systematic literature search identified 44 lesions causing prosopagnosia, only 29 of which intersected the right fusiform face area. However, all 44 lesion locations fell within a single brain network defined by connectivity to the right fusiform face area. Less consistent connectivity was found to other face-selective regions. Surprisingly, all 44 lesion locations were also functionally connected, through negative correlation, with regions in the left frontal cortex. This connectivity pattern was highly reproducible and specific to lesions causing prosopagnosia. Positive connectivity to the right fusiform face area and negative connectivity to left frontal regions were independent predictors of prosopagnosia and predicted subclinical facial agnosia in an independent lesion cohort. We conclude that lesions causing prosopagnosia localize to a single functionally connected brain network defined by connectivity to the right fusiform face area and to left frontal regions. Implications of these findings for models of facial recognition deficits are discussed.

摘要

右侧梭状回面部区域的损伤会破坏识别面孔的能力,这是一个典型的例子,说明了专门的大脑区域损伤如何破坏专门的大脑功能。然而,类似的症状也可能是由其他大脑区域的损伤引起的,现在认为面孔识别依赖于分布式的大脑网络。这个网络的范围以及哪些区域对人脸识别至关重要仍不清楚。在这里,我们根据导致临床显著面孔识别障碍的损伤部位,从经验上推导出这个网络。通过系统的文献检索确定获得性面孔失认症的病例,并将损伤部位映射到共同的大脑图谱上。使用来自健康参与者的静息状态功能连接(n = 1000)识别与每个损伤部位相连的大脑区域网络,这一技术称为损伤网络映射。通过重叠损伤网络,识别导致面孔失认症的损伤的共同连接。使用分半复制评估可重复性。通过与非特异性对照损伤(n = 135)和与非面孔失认症相关的对照损伤(n = 155)进行比较,评估特异性。最后,我们测试了我们从临床明显的面孔失认症病例中得出的面孔识别网络是否可以预测独立损伤队列(n = 31)中的亚临床面孔失认症。我们的系统文献检索确定了 44 个导致面孔失认症的损伤,只有 29 个损伤与右侧梭状回面部区域相交。然而,所有 44 个损伤部位都位于由与右侧梭状回面部区域的连接定义的单个大脑网络内。与其他面部选择区域的连接不太一致。令人惊讶的是,所有 44 个损伤部位也通过负相关与左额皮质的区域功能连接。这种连接模式具有高度的可重复性,并且仅与导致面孔失认症的损伤有关。与右侧梭状回面部区域的正连接和与左额区域的负连接是面孔失认症的独立预测因子,并预测了独立损伤队列中的亚临床面孔失认症。我们得出结论,导致面孔失认症的损伤定位于由与右侧梭状回面部区域和左额区域的连接定义的单个功能连接的大脑网络内。讨论了这些发现对面孔识别缺陷模型的影响。

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