“Bayesian Inferences about the Self (and Others): a Review”, 2014 (; backlinks; similar):
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 optimize the likely outcomes of social interactions.
Technically, we cast this predict-and-optimize as maximizing the chance of favorable outcomes through active inference. Here the utility of outcomes can be conceptualized as prior beliefs about final states. Actions based on interpersonal representations can therefore be understood as minimizing 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 operationalize the study of interpersonal representations in pathological states.