These are the main themes we explore in our research. They all concern the wider question how we achieve flexible, adaptive behaviour.

Learning the Structure of the Environment

This experiment showed the human ability to learn complex relationships between items (Monsters). Both behavioural efficiency and subjective feelings reflected this learning.

The world we live in is not random chaos (phew), we can learn about regularities and use these to make decisions. Learning about the relationship between events is called statistical learning. Statistical knowledge about the relationships of events can provide a pivotal advantage in noticing changes in our environment quickly, and making the right decisions. Recent projects looked at the human ability to learn high-level statistical relationships. New work will test the degree to which the brain’s ability to be a precise statistician allows us to perceive accurately and react quickly when switching between tasks.

Learning from Prediction Errors


This experiment showed that receiving reward activates the brain areas associated with the action that was reinforced.

Knowing something about the structure of our environment allows us to make predictions. This line of research explores the learning that results when what we believe about the environment results in incorrect predictions. A specific focus is on how we learn from reward (reinforcement).

Reinforcement-learning theory offers strong predictions under which conditions we learn from prediction errors, and which brain mechanisms support this type of learning. We put these predictions to the test, most recently in projects which explored how important it is for learning that we’re pleasantly surprised by the reward.

We’re particularly interested in how reward-driven learning modulates how we respond flexibly to changes in the structure of our environment.

Selective Information Processing

In this study, we show that neuronal preparation for colour perception was related to participants’ expectation of doing well – or doing badly.


This new chunk of projects explores how we seek out information from our environment to make the right decisions. Which sources of information do we exploit to learn about the structure of the environment, and what type of prediction errors make us change our predictions? Recent projects have investigated the effect of beliefs on feedback processing. The largest current project explores how we use our internal judgments of how well we’re doing and how confident we are that we know what is happening around us to optimize perception and action. Some projects in this theme are supported by theĀ  Brunel Research & Innovation Fund Award & others by the Royal Society Small Research Grant scheme.

Please refer to the people page to learn more about the network of collaborations and joint efforts in these projects.


Tales from junior researcherettes in Cognitive Science

Attention and Cognitive Control Lab

Nick Yeung's Lab at the University of Oxford.

ResearchBuzz: Firehose

Everything I post on RB and a bit more, in tagged individual posts.

The Replication Network

Furthering the Practice of Replication in Economics

basic statistics

simple steps to improve statistical analyses in neuroscience & psychology