Raphael T. Gerraty

The Periaqueductal Gray Selectively Supports Reversal Learning During a Flexible Discrimination Task in Mice

The paper uses fMRI in mice to show that the periaqueductal gray (PAG) supports reversal learning during a flexible discrimination task by updating value representations.

Two routes to value-based decisions in Parkinsons disease: differentiating incremental reinforcement learning from episodic memory

This study investigates reward-based learning deficits in Parkinson's disease, finding impaired incremental learning but intact episodic memory, with medication improving the deficit.

Hierarchical Bayesian Models of Reinforcement Learning: Introduction and comparison to alternative methods

This paper introduces hierarchical Bayesian modeling as a method to improve out-of-sample prediction in reinforcement learning by simultaneously extracting and imposing empirical priors.

Dopamine modulates learning-related changes in dynamic striatal-cortical connectivity in Parkinson’s disease

This study investigates how dopamine affects dynamic striatal-cortical connectivity during learning in Parkinson’s disease patients, finding dopamine-dependent changes in network flexibility and connectivity.

Dynamic flexibility in striatal-cortical circuits supports reinforcement learning

The paper uses fMRI and dynamic network neuroscience to study how striatal-cortical circuits change during reinforcement learning and finds that dynamic network coupling correlates with learning parameters.