Computational mechanisms underlying latent inverse value updating of unchosen actions

Current studies suggest that individuals estimate the value of their choices based on observed feedback. Here, we ask whether individuals update the value of their unchosen actions, even when the associated feedback remains unknown. Two hundred and three individuals completed a multi-armed bandit task, making choices to gain rewards. We found robust evidence suggesting inverse value updating for unchosen actions based on the chosen action’s outcome. Computational modeling results suggested that this effect is mainly explained by a value updating mechanism whereby individuals integrate the outcome history for choosing an option with that of avoiding the alternative. Properties of the deliberation (i.e., duration/difficulty) did not moderate the latent value updating of unchosen actions, suggesting that memory traces generated during deliberation take a smaller role in this phenomenon than previously thought. We discuss the mechanisms facilitating credit assignment to unchosen actions and their implications for human decision-making.