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Yael Niv

 

Tuesday 31st March 2015

Time: 3.30pm

 

Basement Seminar Room

Alexandra House, 17 Queen Square, London, WC1N 3AR

 

What is the role of the orbitofrontal cortex in reinforcement learning?

 

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 about the effects of dopamine
on learning in the basal ganglia. However, the first ingredient in any
reinforcement learning algorithm is a representation of the task as a
sequence of states. Where do these state representations come from? In
this talk I will first argue, and demonstrate using behavioral
experiments, that animals and humans learn the latent structure of a
task, thus forming a state space through experience. I will then suggest
that the orbitofrontal cortex is critical to representing these state
spaces, especially in tasks whose latent structure is important for
correct performance, and demonstrate how this hypothesis can explain
extant data from studies in which orbitofrontal function was
compromised. Finally, I will present data from a new study in which we
use representation similarity analysis and graph theory to map the
representation of sixteen task states in the human orbitofrontal cortex.