Competitive integration of time and reward explains value-sensitive foraging decisions and frontal cortex ramping dynamics.

Patch foraging presents a ubiquitous decision-making process in which animals decide when to abandon a resource patch of diminishing value to pursue an alternative. We developed a virtual foraging task in which mouse behavior varied systematically with patch value. Mouse behavior could be explained by a model integrating time and rewards antagonistically, scaled by a latent patience state.

Dopamine neurons share common response function for reward prediction error.

Dopamine neurons are thought to signal reward prediction error, or the difference between actual and predicted reward. How dopamine neurons jointly encode this information, however, remains unclear. One possibility is that different neurons specialize in different aspects of prediction error; another is that each neuron calculates prediction error in the same way.

Arithmetic and local circuitry underlying dopamine prediction errors.

Dopamine neurons are thought to facilitate learning by comparing actual and expected reward. Despite two decades of investigation, little is known about how this comparison is made. To determine how dopamine neurons calculate prediction error, we combined optogenetic manipulations with extracellular recordings in the ventral tegmental area while mice engaged in classical conditioning.