Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

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.

Original publication

DOI

10.1016/j.neuron.2011.02.027

Type

Journal article

Journal

Neuron

Publication Date

03/2011

Volume

69

Pages

1204 - 1215

Addresses

Center for Neural Science and Department of Psychology, New York University, New York, NY 10012, USA. daw@cns.nyu.edu

Keywords

Basal Ganglia, Neurons, Humans, Dopamine, Magnetic Resonance Imaging, Brain Mapping, Logistic Models, Reinforcement (Psychology), Choice Behavior, Neuropsychological Tests, Models, Neurological, Adult, Female, Male