Computational heterogeneity in the human mesencephalic dopamine system

Recent evidence in animals has indicated that the mesencephalic dopamine system is heterogeneous anatomically, molecularly, and functionally, and it has been suggested that the dopamine system comprises distinct functional systems. Identifying and characterizing these systems in humans will have widespread ramifications for understanding drug addiction and mental health disorders. Model-based studies in humans have suggested an analogous computational heterogeneity, in which dopaminergic targets in striatum encode both experience-based learning signals and counterfactual learning signals that are based on hypothetical information. We used brainstem-tailored fMRI to identify mesencephalic sources of experiential and counterfactual learning signals. Participants completed a decision-making task based on investing in markets. This sequential investment task generated experience-based learning signals, in the form of temporal difference (TD) reward prediction errors, and counterfactual learning signals, in the form of fictive errors. Fictive errors are reinforcement learning signals based on hypothetical information about what could have been. An additional learning signal was constructed to be relatable to a motivational salience signal. Blood oxygenation level dependent responses in regions of substantia nigra (SN) and ventral tegmental area (VTA), where dopamine neurons are located, coded for TD and fictive errors, and additionally were related to the motivational salience signal. These results are highly consistent with animal electrophysiology and provide direct evidence that human SN and VTA heterogeneously handle important reward-harvesting computations.