TY - JOUR T1 - Dopamine transients delivered in learning contexts do not act as model-free prediction errors JF - bioRxiv DO - 10.1101/574541 SP - 574541 AU - Melissa J. Sharpe AU - Hannah M. Batchelor AU - Lauren E. Mueller AU - Chun Yun Chang AU - Etienne J.P. Maes AU - Yael Niv AU - Geoffrey Schoenbaum Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/03/12/574541.abstract N2 - Dopamine neurons fire transiently in response to unexpected rewards. These neural correlates are proposed to signal the reward prediction error described in model-free reinforcement learning algorithms. This error term represents the unpredicted or ‘excess’ value of the rewarding event. In model-free reinforcement learning, this value is then stored as part of the learned value of any antecedent cues, contexts or events, making them intrinsically valuable, independent of the specific rewarding event that caused the prediction error. In support of equivalence between dopamine transients and this model-free error term, proponents cite causal optogenetic studies showing that artificially induced dopamine transients cause lasting changes in behavior. Yet none of these studies directly demonstrate the presence of cached value under conditions appropriate for associative learning. To address this gap in our knowledge, we conducted three studies where we optogenetically activated dopamine neurons while rats were learning associative relationships, both with and without reward. In each experiment, the antecedent cues failed to acquired value and instead entered into value-independent associative relationships with the other cues or rewards. These results show that dopamine transients, constrained within appropriate learning situations, support valueless associative learning. ER -