Abstract：
Face perception is a complex process that involves highly specialized procedures and mechanisms. Investigating into face perception can help us better understand how the brain processes fine-grained, multidimensional information. This research aimed to delve deeply into how different dimensions of facial information are represented in specific brain regions or through inter-regional connections via an implicit face recognition task. To capture the representation of various facial information in the brain, we employed support vector machine decoding, functional connectivity, and model-based representational similarity analysis on fMRI data, resulting in the identification of three crucial findings. Firstly, despite the implicit nature of the task, emotions were still represented in the brain, contrasting with all other facial information. Secondly, the connection between the medial amygdala and the parahippocampal gyrus was found to be essential for the representation of facial emotion in implicit tasks. Thirdly, in implicit tasks, arousal representation occurred in the parahippocampal gyrus, while valence depended on the connection between the primary visual cortex and the parahippocampal gyrus. In conclusion, these findings dissociate the neural mechanisms of emotional valence and arousal, revealing the precise spatial patterns of multidimensional information processing in faces.
摘要：
人脸感知是一个复杂的过程，涉及高度专业化的程序和机制。对面部感知的研究可以帮助我们更好地理解大脑是如何处理细粒度的，多维信息。这项研究旨在深入研究面部信息的不同维度如何在特定的大脑区域或通过隐式面部识别任务通过区域间连接来表示。为了捕获大脑中各种面部信息的表示，我们采用支持向量机解码，功能连接，和基于模型的功能磁共振成像数据的代表性相似性分析，从而确定了三个重要的发现。首先,尽管任务的内隐性质，情绪仍然表现在大脑中，与所有其他面部信息形成对比。其次,发现内侧杏仁核和海马旁回之间的联系对于内隐任务中面部情绪的表现至关重要。第三，在隐式任务中，唤醒表现发生在海马旁回，而效价取决于初级视觉皮层和海马旁回之间的联系。总之,这些发现分离了情绪效价和唤醒的神经机制，揭示人脸多维信息处理的精确空间模式。
