Dissertations, Theses, and Capstone Projects

Date of Degree


Document Type


Degree Name



Cognitive Neuroscience


Jeff Beeler

Subject Categories

Behavioral Neurobiology | Cognitive Neuroscience


dopamine, GABA, reward-based learning, ventral tegmental area


Ventral tegmental area (VTA) dopamine neurons signal and participate in reward-related learning. Specifically, dopamine is postulated to encode reward-related environmental stimuli to compute reward prediction errors (RPEs). It is through the computation and maintenance of RPEs that learning occurs. However, little is known about the neural mechanisms that underlie how dopamine neurons compute RPEs and facilitate reward-related learning. The present study utilized fiber photometry in conjunction with a Pavlovian reward-based task to identify how GABA inputs to VTA dopamine neurons contribute to the computation of RPEs and reward-based behavior. Activity of GABA inputs to VTA dopamine neurons increased for reward-predicting cues and after the consumption of a food reward. This activity did not emerge until later in learning, signifying how GABA inputs to VTA dopamine neurons change over time. The activity of GABA inputs to VTA dopamine neurons was consistent with the change in dopaminergic activity giving evidence to the theory that GABA inputs play a role in encoding RPE-related information. Photometric recordings coupled with collected behavioral data suggest GABA encodes reward-predicting stimuli and provides this information to dopamine through GABA inputs to compute and update reward prediction errors.