<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>71(6)</volume><submitter>Wunderlich K</submitter><funding>Wellcome Trust</funding><pubmed_abstract>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.</pubmed_abstract><journal>Neuron</journal><pagination>1141-52</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC3183226</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Hedging your bets by learning reward correlations in the human brain.</pubmed_title><pmcid>PMC3183226</pmcid><pubmed_authors>Dolan RJ</pubmed_authors><pubmed_authors>Wunderlich K</pubmed_authors><pubmed_authors>Bossaerts P</pubmed_authors><pubmed_authors>Symmonds M</pubmed_authors></additional><is_claimable>false</is_claimable><name>Hedging your bets by learning reward correlations in the human brain.</name><description>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.</description><dates><release>2011-01-01T00:00:00Z</release><publication>2011 Sep</publication><modification>2020-11-20T10:06:06Z</modification><creation>2019-03-27T00:44:27Z</creation></dates><accession>S-EPMC3183226</accession><cross_references><pubmed>21943609</pubmed><doi>10.1016/j.neuron.2011.07.025</doi></cross_references></HashMap>