Self representation is fundamental to mental functions. While the self has mostly been studied in traditional psychophilosophical terms ('self as subject'), recent laboratory work suggests that the self can be measured quantitatively by assessing biases towards self-associated stimuli ('self as object'). Here, we summarize new quantitative paradigms for assessing the self, drawn from psychology, neuroeconomics, embodied cognition, and social neuroscience. We then propose a neural model of the self as an emerging property of interactions between a core 'self network' (e.g., medial prefrontal cortex; mPFC), a cognitive control network [e.g., dorsolateral (dl)PFC], and a salience network (e.g., insula). This framework not only represents a step forward in self research, but also has important clinical significance, resonating recent efforts in computational psychiatry.

中文翻译：

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自我作为对象：自我研究的新趋势

自我表征是心理功能的基础。虽然自我主要是用传统的心理哲学术语（“自我作为主体”）进行研究的，但最近的实验室工作表明，可以通过评估对自我相关刺激（“自我作为客体”）的偏见来定量测量自我。在这里，我们总结了评估自我的新定量范式，这些范式来自心理学、神经经济学、具身认知和社会神经科学。然后，我们提出了一种自我神经模型，作为核心“自我网络”（例如内侧前额叶皮层；mPFC）、认知控制网络 [例如，背外侧 (dl)PFC] 和显着性网络之间相互作用的新兴属性（例如，绝缘体）。这个框架不仅代表了自我研究的进步，而且具有重要的临床意义，