Overestimating the intensity of negative feelings in autobiographical memory: evidence from the 9/11 attack and COVID-19 pandemic.

When recalling autobiographical events, people not only retrieve event details but also the feelings they experienced. The current study examined whether people are able to consistently recall the intensity of past feelings associated with two consequential and negatively valenced events, i.e.

Causal Inference Gates Corticostriatal Learning.

Attributing outcomes to your own actions or to external causes is essential for appropriately learning which actions lead to reward and which actions do not. Our previous work showed that this type of credit assignment is best explained by a Bayesian reinforcement learning model which posits that beliefs about the causal structure of the environment modulate reward prediction errors (RPEs) during action value updating. In this study, we investigated the brain networks underlying reinforcement learning that are influenced by causal beliefs using functional magnetic resonance imaging while human participants ( = 31; 13 males, 18 females) completed a behavioral task that manipulated beliefs about causal structure.

The rational use of causal inference to guide reinforcement learning strengthens with age.

Beliefs about the controllability of positive or negative events in the environment can shape learning throughout the lifespan. Previous research has shown that adults' learning is modulated by beliefs about the causal structure of the environment such that they update their value estimates to a lesser extent when the outcomes can be attributed to hidden causes. This study examined whether external causes similarly influenced outcome attributions and learning across development.

Publisher Correction: Controllability governs the balance between Pavlovian and instrumental action selection.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Controllability governs the balance between Pavlovian and instrumental action selection.

A Pavlovian bias to approach reward-predictive cues and avoid punishment-predictive cues can conflict with instrumentally-optimal actions. Here, we propose that the brain arbitrates between Pavlovian and instrumental control by inferring which is a better predictor of reward. The instrumental predictor is more flexible; it can learn values that depend on both stimuli and actions, whereas the Pavlovian predictor learns values that depend only on stimuli.