Egocentric biases are predicted by the precision of self-related predictions

Leora Sevi*, Mirta Stantic, Jennifer Murphy, Michel Pierre Coll, Caroline Catmur, Geoffrey Bird*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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According to predictive processing theories, emotional inference involves simultaneously minimising discrepancies between predictions and sensory evidence relating to both one's own and others' states, achievable by altering either one's own state (empathy) or perception of another's state (egocentric bias) so they are more congruent. We tested a key hypothesis of these accounts, that predictions are weighted in inference according to their precision (inverse variance). If correct, increasingly precise self-related predictions should be associated with increasingly biased perception of another's emotional expression. We manipulated predictions about upcoming own-pain (low or high magnitude) using cues that afforded either precise (a narrow range of possible magnitudes) or imprecise (a wide range) predictions. Participants judged pained facial expressions presented concurrently with own-pain to be more intense when own-pain was greater, and precise cues increased this biasing effect. Implications of conceptualising interpersonal influence in terms of predictive processing are discussed.

Original languageEnglish
Pages (from-to)322-332
Number of pages11
Early online date9 Jun 2022
Publication statusPublished - Sept 2022

Bibliographical note

Funding Information:
G. Bird was supported by an ESRC Grant ( ES/R007527/1 ) and the Baily Thomas Charitable Trust.

Publisher Copyright:
© 2022 The Authors


  • Emotion recognition
  • Empathy
  • Generative model
  • Precision
  • Predictive coding
  • Predictive interoceptive coding

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience


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