Action prediction error: a value-free dopaminergic teaching signal that drives stable learning

Francesca Greenstreet,Hernando Martinez Vergara,Yvonne Johansson,Sthitapranjya Pati, Laura Schwarz,Stephen C Lenzi, Matthew Wisdom, Alina Gubanova,Fred Marbach, Lars Rollik, Jasvin Kaur, Theodore Moskovitz, Joseph Cohen, Emmett Thompson,Troy W Margrie,Claudia Clopath,Marcus Stephenson-Jones


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Animals’ choice behavior is characterized by two main tendencies: taking actions that led to rewards and repeating past actions. Theory suggests these strategies may be reinforced by different types of dopaminergic teaching signals: reward prediction error (RPE) to reinforce value-based associations and movement-based action prediction errors to reinforce value-free repetitive associations. Here we use an auditory-discrimination task in mice to show that movement-related dopamine activity in the tail of the striatum encodes the hypothesized action prediction error signal. Causal manipulations reveal that this prediction error serves as a value-free teaching signal that supports learning by reinforcing repeated associations. Computational modeling and experiments demonstrate that action prediction errors alone cannot support reward-guided learning but when paired with the RPE circuitry they serve to consolidate stable sound-action associations in a value-free manner. Together we show that there are two types of dopaminergic prediction errors that work in tandem to support learning. ### Competing Interest Statement The authors have declared no competing interest.
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