Oliver J. Hulme

This study investigates how brain networks reconfigure during reward prediction error processing in different experimental contexts using fMRI.

This study investigates choice history effects in mice and humans, showing they are adaptive and linked to optimal foraging strategies, and introduces a new reinforcement learning model that better predicts behavior.

The paper reviews theories of homeostatic control and evaluates their application to energy homeostasis, proposing a circuit that integrates physiological and behavioral regulation.

The paper investigates how reward prediction error (RPE) signals in brainstem nuclei change with glycemic fluctuations, showing they are modulated by homeostatic state.

The paper shows that four brain regions represent value estimates on different time-scales, interacting to support flexible decision-making.