Dopaminergic prediction errors in the ventral tegmental area reflect a multithreaded predictive model.
Yuji K TakahashiThomas A StalnakerLauren E MuellerSevan K HarootonianAngela J LangdonGeoffrey SchoenbaumPublished in: Nature neuroscience (2023)
Dopamine neuron activity is tied to the prediction error in temporal difference reinforcement learning models. These models make significant simplifying assumptions, particularly with regard to the structure of the predictions fed into the dopamine neurons, which consist of a single chain of timepoint states. Although this predictive structure can explain error signals observed in many studies, it cannot cope with settings where subjects might infer multiple independent events and outcomes. In the present study, we recorded dopamine neurons in the ventral tegmental area in such a setting to test the validity of the single-stream assumption. Rats were trained in an odor-based choice task, in which the timing and identity of one of several rewards delivered in each trial changed across trial blocks. This design revealed an error signaling pattern that requires the dopamine neurons to access and update multiple independent predictive streams reflecting the subject's belief about timing and potentially unique identities of expected rewards.
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