Midbrain dopamine neurons are well known for their role in reward-based reinforcement learning. We found that the activity of dopamine axons in the posterior tail of the striatum (TS) scaled with the novelty and intensity of external stimuli, but did not encode reward value. We demonstrated that the ablation of TS-projecting dopamine neurons specifically inhibited avoidance of novel or high-intensity stimuli without affecting animals' initial avoidance responses, suggesting a role in reinforcement rather than simply in avoidance itself. Furthermore, we found that animals avoided optogenetic activation of dopamine axons in TS during a choice task and that this stimulation could partially reinstate avoidance of a familiar object. These results suggest that TS-projecting dopamine neurons reinforce avoidance of threatening stimuli. More generally, our results indicate that there are at least two axes of reinforcement learning using dopamine in the striatum: one based on value and one based on external threat.

Different regions of the striatum regulate different types of behavior. However, how dopamine signals differ across striatal regions and how dopamine regulates different behaviors remain unclear. Here, we compared dopamine axon activity in the ventral, dorsomedial, and dorsolateral striatum, while mice performed a perceptual and value-based decision task. Surprisingly, dopamine axon activity was similar across all three areas. At a glance, the activity multiplexed different variables such as stimulus-associated values, confidence, and reward feedback at different phases of the task. Our modeling demonstrates, however, that these modulations can be inclusively explained by moment-by-moment changes in the expected reward, that is the temporal difference error. A major difference between areas was the overall activity level of reward responses: reward responses in dorsolateral striatum were positively shifted, lacking inhibitory responses to negative prediction errors. The differences in dopamine signals put specific constraints on the properties of behaviors controlled by dopamine in these regions.

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Animals exhibit diverse behavioral responses, such as exploration and avoidance, to novel cues in the environment. However, it remains unclear how dopamine neuron-related novelty responses influence behavior. Here, we characterized dynamics of novelty exploration using multi-point tracking (DeepLabCut) and behavioral segmentation (MoSeq). Novelty elicits a characteristic sequence of behavior, starting with investigatory approach and culminating in object engagement or avoidance. Dopamine in the tail of striatum (TS) suppresses engagement, and dopamine responses were predictive of individual variability in behavior. Behavioral dynamics and individual variability were explained by a novel reinforcement learning (RL) model of threat prediction, in which behavior arises from a novelty-induced initial threat prediction (akin to shaping bonus), and a threat prediction that is learned through dopamine-mediated threat prediction errors. These results uncover an algorithmic similarity between reward- and threat-related dopamine sub-systems.

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