Moorthy Ganeshkumar

This study shows that hippocampal reward representations become predictive of reward over time as mice learn a reward-based task.

This paper develops a recurrent neural network-based reinforcement learning framework to model decision-making deficits in schizophrenia, revealing suboptimal belief updating linked to neural dysfunction.

This paper develops a normative model of place field reorganization during reward maximization, showing it unifies navigation phenomena and improves policy learning.