Bayesian inferences about the self (and others): a review

Conscious Cogn. 2014 Apr;25(100):67-76. doi: 10.1016/j.concog.2014.01.009. Epub 2014 Feb 25.


Viewing the brain as an organ of approximate Bayesian inference can help us understand how it represents the self. We suggest that inferred representations of the self have a normative function: to predict and optimise the likely outcomes of social interactions. Technically, we cast this predict-and-optimise as maximising the chance of favourable outcomes through active inference. Here the utility of outcomes can be conceptualised as prior beliefs about final states. Actions based on interpersonal representations can therefore be understood as minimising surprise - under the prior belief that one will end up in states with high utility. Interpersonal representations thus serve to render interactions more predictable, while the affective valence of interpersonal inference renders self-perception evaluative. Distortions of self-representation contribute to major psychiatric disorders such as depression, personality disorder and paranoia. The approach we review may therefore operationalise the study of interpersonal representations in pathological states.

Keywords: Active inference; Free energy minimisation; Other-representation; Paranoia; Personality disorder; Self-representation.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Bayes Theorem*
  • Humans
  • Interpersonal Relations*
  • Personality Disorders
  • Personality*
  • Self Concept*
  • Social Perception*