Self as Object: Emerging Trends in Self Research

Jie Sui* (Corresponding Author), Xiaosi Gu

*Corresponding author for this work

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

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


Original languageEnglish
Pages (from-to)643-653
Number of pages11
JournalTrends in Neurosciences
Volume40
Issue number11
Early online date5 Oct 2017
DOIs
Publication statusPublished - Nov 2017

Keywords

  • self
  • other
  • objective measures
  • computational psychiatry
  • self network

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