Elucidating the Basal Ganglia Circuits for Reward Expectation

Predicting future outcomes is fundamental for adaptive behaviour. Reward-predicting stimuli evoke a state of expectation, which informs motivation, guides attention, and drives preparatory motor behaviour. Reward expectations are crucial for learning since they serve as a comparison to actual outcomes. This comparison allows animals to determine if there is a prediction error (i.e. if an outcome was better or worse than expected). Even though reward expectation signals are observed in many areas of the brain how they are computed remains unknown. The main reason for lack of progress is the absence of a clear understanding of where expectation is generated and which circuits are involved in its computation. Consequently, we are missing the prerequisite knowledge for determining where reward expectation arises, how it is computed, and how expectations are learnt. We hypothesize, based on preliminary data and prior literature, that specific circuits within the basal ganglia are crucial for computing reward expectation. We will utilize cutting edge viral methods, combined with electrophysiological recordings and calcium imaging techniques, to identify the specific circuits and cell-types within the basal ganglia nuclei that compute reward expectation. The causal role these identified circuits play in learning will be determined using cell-type specific manipulations in mice performing reinforcement learning tasks. Finally, we will pioneer approaches to manipulate elements of the basal ganglia circuit, while simultaneously recording from specific cell types in the ventral tegmental area, that are involved in computing reward prediction error. Together, this work will uncover how specific basal ganglia cell types causally contribute to the computation of reward expectation and the calculation of reward prediction error. This will provide a foundation for understating how reward expectation influences adaptive behaviour and is perturbed in psychiatric disease.