A task-invariant prior explains trial-by-trial active avoidance behaviour across gain and loss tasks - Tobias Granwald; Peter Dayan; Máté Lengyel; Marc Guitart-Masip (Communications Psychology)
Abstract Failing to make decisions that would actively avoid negative outcomes is central to helplessness. In a Bayesian framework, deciding whether to act is informed by beliefs about the world that can be characterised as priors. However, these priors have not been previously quantified. Here we administered two tasks in which 279 participants decided whether to attempt active avoidance actions. In both tasks, participants decided between a passive option that would for sure result in a negative outcome of varying size, and a costly active option that allowed them a probability of avoiding the negative outcome. The tasks differed in framing and valence, allowing us to test whether the prior generating biases in behaviour is problem-specific or task-independent and general. We performed extensive comparisons of models offering different structural explanations of the data, finding that a Bayesian model with a task-invariant prior for active avoidance provided the best fit to participants’ trial-by-trial behaviour. The parameters of this prior were reliable, and participants’ self-rated positive affect was weakly correlated with this prior such that participants with an optimistic prior reported higher levels of positive affect. These results show that individual differences in prior beliefs can explain decisions to engage in active avoidance of negative outcomes, providing evidence for a Bayesian conceptualization of helplessness.