Bayesian inferences about the self (and others): A review
Keywords: personality disorder, paranoia, self-representation, Other-representation, Free energy minimisation, Active inference
Abstract
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. (C) 2014 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/).
Más información
Título según WOS: | Bayesian inferences about the self (and others): A review |
Título de la Revista: | CONSCIOUSNESS AND COGNITION |
Volumen: | 25 |
Editorial: | ACADEMIC PRESS INC ELSEVIER SCIENCE |
Fecha de publicación: | 2014 |
Página de inicio: | 67 |
Página final: | 76 |
Idioma: | English |
DOI: |
10.1016/j.concog.2014.01.009 |
Notas: | ISI - ISI |