State dependent information processing in reward circuitry

For both survival and procreation, animals must facilitate behavior that results in beneficial outcomes, and inhibit behavior that results in harmful outcomes. Inherent to this process is the ability of animals to predict probable outcomes that are associated with stimuli and behavior. Neurons in reward-related brain structures respond to stimuli and behavior in a manner that reflects the probable outcomes that are associated with those stimuli and behavior. Although these responses have been characterized in prior research, one issue has received relatively little attention: Outcomes depend on more than stimuli and behavior alone. Outcomes also depend on long-lasting aspects of the animals state, including context, physiological states, and emotional states. It is not clear how such state-dependent information is represented in reward circuitry. The main focus of this thesis was to investigate this issue. We demonstrate that neurons exhibit long-lasting changes in average firing rate that can be sufficient for representing state-dependent information. In addition, we report that these changes in average firing rate can act as a gain control to modulate the magnitude of neural responses to stimuli and behavior. In this way, individual neurons can both represent state-dependent information, and use this information to modulate representations of outcomes associated with stimuli and behavior.