Self as Object: Emerging Trends in Self Research

Jie Sui, Xiaosi Gu

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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. New paradigms have emerged from psychology, neuroeconomics, embodied cognition, and social neuroscience that provide objective measures of the self.Neuroimaging and neuropsychological studies using these new paradigms have revealed central roles for three brain networks in self-processing: a core 'self network' (medial prefrontal regions), a cognitive control network (lateral PFC and superior temporal sulcus), and a salience network (insula, amygdala, and striatum).Self-processing has also been gaining increased attention in neuropsychiatric research, because initial evidence suggests the self is altered in almost all psychiatric disorders, including depression, schizophrenia, and personality disorders.

Original languageEnglish
Pages (from-to)643-653
JournalTrends in Neurosciences
Issue number11
Early online date5 Oct 2017
Publication statusPublished - 1 Nov 2017


  • Computational psychiatry
  • Objective measures
  • Other
  • Self
  • Self network

ASJC Scopus subject areas

  • Neuroscience(all)


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