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Processing speed enhances model-based over model-free reinforcement learning in the presence of high working memory functioning

  • Theories of decision-making and its neural substrates have long assumed the existence of two distinct and competing valuation systems, variously described as goal-directed vs. habitual, or, more recently and based on statistical arguments, as model-free vs. model-based reinforcement-learning. Though both have been shown to control choices, the cognitive abilities associated with these systems are under ongoing investigation. Here we examine the link to cognitive abilities, and find that individual differences in processing speed covary with a shift from model-free to model-based choice control in the presence of above-average working memory function. This suggests shared cognitive and neural processes; provides a bridge between literatures on intelligence and valuation; and may guide the development of process models of different valuation components. Furthermore, it provides a rationale for individual differences in the tendency to deploy valuation systems, which may be important for understanding the manifold neuropsychiatricTheories of decision-making and its neural substrates have long assumed the existence of two distinct and competing valuation systems, variously described as goal-directed vs. habitual, or, more recently and based on statistical arguments, as model-free vs. model-based reinforcement-learning. Though both have been shown to control choices, the cognitive abilities associated with these systems are under ongoing investigation. Here we examine the link to cognitive abilities, and find that individual differences in processing speed covary with a shift from model-free to model-based choice control in the presence of above-average working memory function. This suggests shared cognitive and neural processes; provides a bridge between literatures on intelligence and valuation; and may guide the development of process models of different valuation components. Furthermore, it provides a rationale for individual differences in the tendency to deploy valuation systems, which may be important for understanding the manifold neuropsychiatric diseases associated with malfunctions of valuation.show moreshow less

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Author details:Daniel SchadORCiDGND, Elisabeth Juenger, Miriam Hannah SeboldORCiDGND, Maria GarbusowORCiDGND, Nadine BernhardtORCiD, Amir-Homayoun Javadi, Ulrich S. Zimmermann, Michael N. SmolkaORCiDGND, Andreas HeinzORCiDGND, Michael Armin RappORCiDGND, Quentin J. M. HuysORCiD
DOI:https://doi.org/10.3389/fpsyg.2014.01450
ISSN:1664-1078
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/25566131
Title of parent work (English):Frontiers in psychology
Publisher:Frontiers Research Foundation
Place of publishing:Lausanne
Publication type:Article
Language:English
Year of first publication:2014
Publication year:2014
Release date:2017/03/26
Tag:cognitive abilities; decision-making; fluid intelligence; habitual and goal-directed system; model-based and model-free learning; reward
Volume:5
Number of pages:10
Organizational units:Humanwissenschaftliche Fakultät / Strukturbereich Kognitionswissenschaften / Department Psychologie
Peer review:Referiert
Publishing method:Open Access
Institution name at the time of the publication:Humanwissenschaftliche Fakultät / Institut für Psychologie
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