PDF(Pubmed)
Abstract：
We report an investigation of the neural processes involved in the processing of faces and objects of brain-lesioned patient PS, a well-documented case of pure acquired prosopagnosia. We gathered a substantial dataset of high-density electrophysiological recordings from both PS and neurotypicals. Using representational similarity analysis, we produced time-resolved brain representations in a format that facilitates direct comparisons across time points, different individuals, and computational models. To understand how the lesions in PS\'s ventral stream affect the temporal evolution of her brain representations, we computed the temporal generalization of her brain representations. We uncovered that PS\'s early brain representations exhibit an unusual similarity to later representations, implying an excessive generalization of early visual patterns. To reveal the underlying computational deficits, we correlated PS\' brain representations with those of deep neural networks (DNN). We found that the computations underlying PS\' brain activity bore a closer resemblance to early layers of a visual DNN than those of controls. However, the brain representations in neurotypicals became more akin to those of the later layers of the model compared to PS. We confirmed PS\'s deficits in high-level brain representations by demonstrating that her brain representations exhibited less similarity with those of a DNN of semantics.
摘要：
我们报告了对脑部病变患者PS的面部和物体处理所涉及的神经过程的调查，一个有据可查的纯获得性prosopagnosis病例.我们从PS和神经典型中收集了大量的高密度电生理记录数据集。使用代表性相似性分析，我们以一种有助于直接比较时间点的格式产生了时间分辨的大脑表示，不同的个体,和计算模型。为了了解PS腹侧的病变如何影响她大脑表征的时间演变，我们计算了她大脑表征的时间概括。我们发现PS的早期大脑表现与后来的表现有不同寻常的相似性，暗示对早期视觉模式的过度概括。为了揭示潜在的计算缺陷，我们将PS\'大脑表示与深度神经网络(DNN)的表示相关联。我们发现，与对照组相比，PS脑活动的基础计算与视觉DNN的早期层更相似。然而,与PS相比，神经典型的大脑表现变得更类似于模型的后几层。通过证明她的大脑表示与语义DNN的相似性较小，我们证实了PS在高级大脑表示中的缺陷。
