Will and colleagues recently applied reinforcement learning models to characterise the neural mechanisms of self esteem (Will et al., 2017). They drew on principles from RLT to provide a novel psychological and computational account of how self-esteem develops over time, influenced by appraisals from others (Will et al., 2017). Participants received positive and negative feedback from other people that was allegedly related to an online profile of the participant set up before the study. Over time, participants learned to predict the other’s evaluation of them. Every few trials, participants also rated how good they felt about themselves. Will et al (2017) found that participants felt more positive about themselves if they received positive feedback from others. Importantly, they felt this even more if that positive feedback was unexpected. In other words, a social prediction error - the difference between experienced and expected approval by others - shaped their self-esteem.
