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Human subjects are proficient at tracking the mean and variance of rewards and updating these via prediction errors. Here, we addressed whether humans can also learn about higher-order relationships between distinct environmental outcomes, a defining ecological feature of contexts where multiple sources of rewards are available. By manipulating the degree to which distinct outcomes are correlated, we show that subjects implemented an explicit model-based strategy to learn the associated outcome correlations and were adept in using that information to dynamically adjust their choices in a task that required a minimization of outcome variance. Importantly, the experimentally generated outcome correlations were explicitly represented neuronally in right midinsula with a learning prediction error signal expressed in rostral anterior cingulate cortex. Thus, our data show that the human brain represents higher-order correlation structures between rewards, a core adaptive ability whose immediate benefit is optimized sampling.

Original publication

DOI

10.1016/j.neuron.2011.07.025

Type

Journal article

Journal

Neuron

Publication Date

22/09/2011

Volume

71

Pages

1141 - 1152

Keywords

Adolescent, Adult, Brain, Choice Behavior, Environment, Female, Humans, Learning, Magnetic Resonance Imaging, Male, Models, Neurological, Neuropsychological Tests, Reward, Young Adult