Model-Based Influences on Humans' Choices and Striatal Prediction Errors
The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based pla...
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Veröffentlicht in: | Neuron (Cambridge, Mass.) Mass.), 2011-03, Vol.69 (6), p.1204-1215 |
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Zusammenfassung: | The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making.
► Humans learn both a world model and reinforcement-driven choice preferences ► BOLD responses in striatum and prefrontal cortex reflect both sorts of learning ► Across subjects, striatal BOLD tracks individual differences in model use ► Unexpectedly, ventral striatum shows combined model-based/free influences |
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ISSN: | 0896-6273 1097-4199 1097-4199 |
DOI: | 10.1016/j.neuron.2011.02.027 |