“To do or not to do” is a fundamental decision that has to be made in daily life. Behaviors
related to multiple “to do” choice tasks have long been explained by reinforcement learning …

Reinforcement learning causes an action that yields a positive outcome more likely to be
taken in the future. Here, we investigate how the time elapsed from an action affects …

Reinforcement learning makes an action that yielded a positive outcome more likely to be
taken in the future. Here, we investigate how the time elapsed from an action affects …

In reinforcement learning (RL) experiments, participants learn to make rewarding choices in
response to different stimuli; RL models use outcomes to estimate stimulus–response values …

Reinforcement learning models have long promised to unify computational, psychological
and neural accounts of appetitively conditioned behavior. However, the bulk of data on …

Humans and animals are endowed with a large number of effectors. Although this enables
great behavioral flexibility, it presents an equally formidable reinforcement learning problem …

In reinforcement learning (RL) experiments, participants learn to make rewarding choices in
response to different stimuli; RL models use outcomes to estimate stimulus-response values …

How do we make good decisions in uncertain environments? In psychology and
neuroscience, the classic answer is that we calculate the value of each option and then …

The extent to which subjective awareness influences reward processing, and thereby affects
future decisions, is currently largely unknown. In the present report, we investigated this …

Learning to make rewarding choices in response to stimuli depends on a slow but steady
process, reinforcement learning, and a fast and flexible, but capacity-limited process …