Uncertainty-dependent learning bias in value-based decision making

Do we preferentially learn from positive rather than negative decision outcomes? Previous studies indicated that such bias characterises learning during simple reward learning tasks. However, no research has yet confirmed whether learning bias is also present during sequential decision making under uncertainty. To fill this gap, we utilised a complex yet ecologically valid paradigm, the Balloon Analogue Risk Task (BART), which measures risk-taking propensity under uncertainty in everyday decision making. Comparing learning from positive and negative outcomes in the BART has been made possible by the Scaled Target Learning model, which characterises both risk-taking propensity and sensitivity to wins and losses. For the first time, we applied this model to a modified BART paradigm with different levels of perceived uncertainty. Crucially, our analyses revealed learning bias during high levels of uncertainty, under which condition bias was negatively tied to task performance. Furthermore, increased sensitivity to wins compared to losses was linked to more risk-seeking behaviour across all conditions, suggesting that learning bias could mediate risky behaviour. Overall, our results contribute to a more accurate characterisation of reward learning behaviour and suggest that learning bias arises when the level of perceived uncertainty surges.