Abstract
Low self-esteem is a risk factor for a range of psychiatric disorders. From a cognitive perspective a negative self-image can be maintained through aberrant learning about self-worth derived from social feedback. We previously showed that neural teaching signals that represent the difference between expected and actual social feedback (i.e., social prediction errors) drive fluctuations in self-worth. Here, we used model-based functional magnetic resonance imaging (fMRI) to characterize learning from social prediction errors in 61 participants drawn from a population-based sample (n = 2402) who were recruited on the basis of being in the bottom or top 10% of self-esteem scores. Participants performed a social evaluation task during fMRI scanning, which entailed predicting whether other people liked them as well as the repeated provision of reported feelings of self-worth. Computational modeling results showed that low self-esteem participants had persistent expectations that others would dislike them, and a reduced propensity to update these expectations in response to social prediction errors. Low self-esteem subjects also displayed an enhanced volatility in reported feelings of self-worth, and this was linked to an increased tendency for social prediction errors to determine momentary self-worth. Canonical correlation analysis revealed that individual differences in self-esteem related to several interconnected psychiatric symptoms organized around a single dimension of interpersonal vulnerability. Such interpersonal vulnerability was associated with an attenuated social value signal in ventromedial prefrontal cortex when making predictions about being liked, and enhanced dorsal prefrontal cortex activity upon receipt of social feedback. We suggest these computational signatures of low self-esteem and their associated neural underpinnings might represent vulnerability for development of psychiatric disorder.
Highlights
Low self-esteem is a core symptom of a range of common mental health problems1,2
This study shows that participants with low self-esteem have a reduced tendency to use social feedback to learn how much they are liked by others, coupled with an enhanced tendency to use social feedback in determining subjective reports of self-worth
Computational modeling revealed these individual differences arise out of differential weighting of social approval prediction errors (SPEs) in updating exectations about being liked, compared to feelings of self-worth. This dissociation between expectations about being liked and feelings of self-worth was paralleled at a neural level and this became especially clear upon taking a dimensional approach
Summary
Low self-esteem is a core symptom of a range of common mental health problems. People with low global self-esteem, an overall negative evaluation of self-worth, exhibit cognitive biases that are thought to contribute to the maintenance of a negative self-image. Those with low self-esteem have expectations that others will view them in a negative light and their feelings of self-worth are more responsive to social feedback. Persistent negative self-views and instability in feelings of self-worth are linked to onset and maintenance of psychiatric disorders, including depression, anxiety and psychosis. We use computational modeling and functional magnetic resonance imaging (fMRI) to ask how low global selfesteem impacts on learning about the self during social evaluation.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
