Neuron 69 (6):1204-1215 (2011)
AbstractThe 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
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Not All Who Ponder Count Costs: Arithmetic Reflection Predicts Utilitarian Tendencies, but Logical Reflection Predicts Both Deontological and Utilitarian Tendencies.Nick Byrd & Paul Conway - 2019 - Cognition 192 (103995).
Computational Psychiatry.P. Read Montague, Raymond J. Dolan, Karl J. Friston & Peter Dayan - 2012 - Trends in Cognitive Sciences 16 (1):72-80.
Above and Beyond the Concrete: The Diverse Representational Substrates of the Predictive Brain.Michael Gilead, Yaacov Trope & Nira Liberman - 2020 - Behavioral and Brain Sciences 43:1-63.
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