Arguably, the most difficult part of learning is deciding what to learn about. Should I
associate the positive outcome of safely completing a street-crossing with the situation 'the …

Compact representations of the environment allow humans to behave efficiently in a
complex world. Reinforcement learning models capture many behavioral and neural effects …

Little is known about the relationship between attention and learning during decision
making. Using eye tracking and multivariate pattern analysis of fMRI data, we measured …

In recent years, ideas from the computational field of reinforcement learning have
revolutionized the study of learning in the brain, famously providing new, precise theories of …

The central theme of this review is the dynamic interaction between information selection
and learning. We pose a fundamental question about this interaction: How do we learn what …

Human decision making is plagued by systematic errors that can have devastating
consequences. Previous research has found that such errors can be partly prevented by …

Biological intelligence is remarkable in its ability to produce complex behaviour in many
diverse situations through data efficient, generalisable and transferable skill acquisition. It is …

Learning usually improves the accuracy of beliefs through the accumulation of experience.
But are there limits to learning that prevent us from accurately understanding our world? In …

In neuroscience, attention has been shown to bidirectionally interact with reinforcement
learning (RL) to reduce the dimensionality of task representations, restricting computations …

Identifying goal-relevant features in novel environments is a central challenge for efficient
behaviour. We asked whether humans address this challenge by relying on prior knowledge …