Topic: Reward representation

Dopaminergic reward prediction error neurons in the midbrain are the most prominent reward representation in the brain. To understand why these neurons represent rewards the way they do when stochastic rewards are encountered, we derive the optimal population of neurons to encode rewards drawn from a given distribution. To do so, we extend an existing framework for efficient coding to decouple the density of neurons from their slopes. We compare the optimally efficient population to measurements of reward prediction error neurons. We find three aspects of the optimized population confirmed: Fi

The concept of a cognitive map posits that the brain maintains an internal representation of space. This map is represented in cells of the hippocampus and entorhinal cortex, which carry information about the animal’s location in an environment. These representations are adaptable to changes in the environment; for example, the number of hippocampal place cells that encode a particular location will increase if a reward is delivered at that location. We aimed to investigate what information the two regions of the entorhinal cortex – medial and lateral – may contribute during reward-guided spat