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 language | English |
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Pages (from-to) | 643-653 |
Number of pages | 11 |
Journal | Trends in Neurosciences |
Volume | 40 |
Issue number | 11 |
Early online date | 5 Oct 2017 |
DOIs | |
Publication status | Published - Nov 2017 |
Keywords
- self
- other
- objective measures
- computational psychiatry
- self network