A prevalent explanation for the self-reference effect is that self-knowledge is represented by a set of specific brain regions, including anterior cingulate cortex (ACC), middle frontal gyrus (MFG), superior temporal gyrus (STG), precuneus, and inferior parietal lobule (IPL), which enables self-knowledge to be processed in priority than other-knowledge. However, the conventional univariate activation analysis adopted by previous studies could only detect the activation of separate brain regions. The current study mainly investigated the global neural patterns of self-knowledge (relative to other-knowledge) by the multivariate pattern analysis (MVPA). Results obtained in Experiments 1 and 2 were highly consistent, indicating that the core self-network (mainly the ACC) and salience network (mainly the insula) could distinguish self-knowledge from other-knowledge. Furthermore, the neural pattern of positive self-knowledge mainly included the ventral part of ACC, while the neural pattern of negative self-knowledge mainly included the ventral and dorsal parts of ACC and cognitive control network (dorsolateral prefrontal cortex: dlPFC). These findings suggest that the core self-network and salience network are specific to the neural process of self-knowledge. Moreover, both positive and negative self-knowledge are separately driven by different cognitive and neural characteristics.

自我参照效应的一个普遍解释是，自我知识由一组特定的大脑区域表示，包括前扣带回皮层 (ACC)、额中回 (MFG)、颞上回 (STG)、楔前叶和下皮层。顶叶小叶（IPL），它使自我知识能够比其他知识优先处理。然而，以往研究采用的传统单变量激活分析只能检测不同大脑区域的激活。目前的研究主要通过多元模式分析（MVPA）来研究自我知识（相对于其他知识）的全局神经模式。实验 1 和 2 中获得的结果高度一致，表明核心自网络（主要是 ACC）和显着网络（主要是脑岛）可以区分自我知识和其他知识。此外，积极自我知识的神经模式主要包括ACC的腹侧部分，而消极自我知识的神经模式主要包括ACC的腹侧和背侧部分和认知控制网络（背外侧前额叶皮层：dlPFC）。这些发现表明核心自我网络和显着性网络特定于自我知识的神经过程。此外，积极和消极的自我知识分别由不同的认知和神经特征驱动。而消极自我认知的神经模式主要包括ACC的腹侧和背侧部分和认知控制网络（背外侧前额叶皮层：dlPFC）。这些发现表明核心自我网络和显着性网络特定于自我知识的神经过程。此外，积极和消极的自我知识分别由不同的认知和神经特征驱动。而消极自我认知的神经模式主要包括ACC的腹侧和背侧部分和认知控制网络（背外侧前额叶皮层：dlPFC）。这些发现表明核心自我网络和显着性网络特定于自我知识的神经过程。此外，积极和消极的自我知识分别由不同的认知和神经特征驱动。