Abstract
During our daily lives, we often learn about the similarity of the traits and preferences of others to our own and use that information during our social interactions. However, it is unclear how the brain represents similarity between the self and others. One possible mechanism is to track similarity to oneself regardless of the identity of the other (Similarity account); an alternative is to track each other person in terms of consistency of their choice similarity with respect to the choices they have made before (consistency account). Our study combined functional Magnetic Resonance Imaging (fMRI) and computational modelling of reinforcement learning (RL) to investigate the neural processes that underlie learning about preference similarity. Participants chose which of two pieces of artwork they preferred and saw the choices of one agent who usually shared their preference and another agent who usually did not. We modelled neural activation with RL models based on the similarity and consistency accounts. Our results showed that activity in brain areas linked to reward and social cognition followed the consistency account. Our findings suggest that impressions of other people can be calculated in a person-specific manner, which assumes that each individual behaves consistently with their past choices.
Original language | English |
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Pages (from-to) | 1061-1072 |
Number of pages | 12 |
Journal | Social Cognitive and Affective Neuroscience |
Volume | 14 |
Issue number | 10 |
DOIs | |
State | Published - 2 Jan 2020 |
Bibliographical note
Publisher Copyright:© 2020 The Author(s) 2020. Published by Oxford University Press. All rights reserved.
Keywords
- fMRI
- prediction error
- reinforcement learning
- self
- social cognition
- Learning/physiology
- Attitude
- Humans
- Brain/physiology
- Male
- Young Adult
- Magnetic Resonance Imaging
- Algorithms
- Social Behavior
- Computer Simulation
- Reinforcement, Psychology
- Adult
- Female
- Reward
ASJC Scopus subject areas
- Experimental and Cognitive Psychology
- Cognitive Neuroscience