How do we make decisions?  

How do we learn from their outcomes? 

 

Current research topics include: 

1) Causal Learning - How does the brain attribute causal responsibility for important outcomes (such as an especially rewarding or aversive experience) to our past choices or to other environmental factors? Go to relevant papers

2) Structure Learning - How does the brain form and tune predictive models of structured environments – such as environments organized hierarchically or as ring structures – and leverage these models to generalize to new contexts that share structural properties? Go to relevant papers

3) Domain Generality of Prediction and Selection Systems - What are the domain-general and domain-specific prediction and decision neural systems in the brain? How do these neural systems interact to give rise to our decisions? Go to relevant papers  

4)  Behavioral Adaptation - How does the brain adapt between behavioral modes or strategies, such as between engaging in a default behavior and exploring the environment to discover potentially better outcomes? Go to relevant papers

To tackle these questions, we integrate computational modeling of behavior and neural processes with functional brain imaging techniques (fMRI, DWI, EEG), intracranial neuronal recording in neurosurgical patients (iEEG), and behavioral experiments in both healthy individuals and patients. While our focus is on how the healthy human brain learns and makes decisions, we also apply the paradigms and computational models we develop and the insights we gain in health to investigate the neural basis of impairments in relevant psychiatric and neurological disorders. 

Key Collaborators: Tim Behrens (Oxford, UCL), Jill O'Reilly (Oxford), Zeb Kurth-Nelson (UCL, Deep Mind), Ray Dolan (UCL), Peter Dayan (UCL), Antonio Rangel (Caltech), Itzhak Fried (UCLA)