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Cognitive control predicts use of model-based reinforcement learning.

Author(s): Otto, A. Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D.

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dc.contributor.authorOtto, A. Ross-
dc.contributor.authorSkatova, Anya-
dc.contributor.authorMadlon-Kay, Seth-
dc.contributor.authorDaw, Nathaniel D.-
dc.date.accessioned2020-02-14T19:44:02Z-
dc.date.available2020-02-14T19:44:02Z-
dc.date.issued2015-02en_US
dc.identifier.citationOtto, A Ross, Skatova, Anya, Madlon-Kay, Seth, Daw, Nathaniel D. (2015). Cognitive control predicts use of model-based reinforcement learning. Journal of Cognitive Neuroscience, 27 (2), 319 - 333. doi:10.1162/jocn_a_00709en_US
dc.identifier.issn0898-929X-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr19x9s-
dc.description.abstractAccounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior.en_US
dc.format.extent319 - 333en_US
dc.languageengen_US
dc.language.isoen_USen_US
dc.relation.ispartofJournal of Cognitive Neuroscienceen_US
dc.rightsFinal published version. Article is made available in OAR by the publisher's permission or policy.en_US
dc.titleCognitive control predicts use of model-based reinforcement learning.en_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1162/jocn_a_00709-
dc.identifier.eissn1530-8898-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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