Can we recognize faces with zero experience on faces? This question is critical because it examines the role of experiences in the formation of domain-specific modules in the brain. Investigation with humans and non-human animals on this issue cannot easily dissociate the effect of the visual experience from that of the hardwired domain-specificity. Therefore the present study built a model of selective deprivation of the experience on faces with a representative deep convolutional neural network, AlexNet, by removing all images containing faces from its training stimuli. This model did not show significant deficits in face categorization and discrimination, and face-selective modules automatically emerged. However, the deprivation reduced the domain-specificity of the face module. In sum, our study provides empirical evidence on the role of nature versus nurture in developing the domain-specific modules that domain-specificity may evolve from non-specific experience without genetic predisposition, and is further fine-tuned by domain-specific experience.

中文翻译：

---

人脸模块出现在深度卷积神经网络中，被有选择地剥夺了人脸体验

我们可以识别出零体验的面孔吗？这个问题至关重要，因为它检查了经验在大脑中特定域模块的形成中的作用。在此问题上与人类和非人类动物进行的调查无法轻松地将视觉体验的效果与硬连线领域特异性的效果区分开。因此，本研究通过从训练刺激中删除所有包含面部的图像，建立了一个具有代表性的深层卷积神经网络AlexNet的面部模型选择性剥夺经验的模型。该模型在面部分类和辨别上没有显示出明显的缺陷，并且自动出现了面部选择模块。但是，剥夺降低了面部模块的域特定性。总共，