Erie Boorman, D. Phil.

 Erie  Boorman, D. Phil.

Position

  • Assistant Professor
  • Psychology

Neural mechanisms of reinforcement-guided learning and decision making

Research Summary

How do we make decisions? How do we learn from their outcomes? My lab seeks mechanistic answers to such questions at the behavioural, computational, and neural systems levels. Our research is multi-disciplinary, lying at the intersection between Psychology, Neuroscience, Artificial Intelligence, and Behavioral Economics. 

We investigate how the human brain forms and tunes predictive models of the environment, and how it leverages these models to make decisions and perform inference. The prediction problems we study span reward prediction (e.g. money, foods, etc.), social prediction (e.g. other people’s intentions, traits, etc.), and “state” prediction (e.g. perceptually signaled contexts, inferred latent contexts). 

Selected Publications

Boorman, E.D., Rajendran, V., O’Reilly, J.X., Behrens, T.E. (2016). Two computationally and anatomically distinct learning signals predict changes to stimulus-outcome associations in hippocampus. Neuron: 89:1343-54.
 
Hill, M.R., Boorman, E.D., Fried, I. (2016). Observational learning computations in single neurons of the human anterior cingulate cortex. Nature Communications: 7:12722. 
 
Boorman, E.D., O’Doherty, J.P., Adolphs, R., Rangel, A. (2013). The behavioral and neural mechanisms underlying the tracking of expertise. Neuron: 80:1558-71. 
 
Boorman, E.D., Behrens, T.E., Woolrich, M.W., and Rushworth, M.F.S. (2009). How green is the grass on the other side? Frontopolar cortex and the representation of alternative courses of action. Neuron, 62:733-43. 

Affiliations

Psychology

Center for Mind and Brain

Neuroscience Graduate Group

UCL-Max Planck Centre for Computational Psychiatry and Ageing Research