• search hit 1 of 4
Back to Result List

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

Export metadata

Additional Services

Share in Twitter Search Google Scholar Statistics
Metadaten
Author:Daniel Johannes Schad, Elisabeth Juenger, Miriam Sebold, Maria Garbusow, Nadine Bernhardt, Amir-Homayoun Javadi, Ulrich S. Zimmermann, Michael N. Smolka, Andreas Heinz, Michael Armin RappORCiDGND, Quentin J. M. Huys
DOI:https://doi.org/10.3389/fpsyg.2014.01450
ISSN:1664-1078 (print)
Pubmed Id:http://www.ncbi.nlm.nih.gov/pubmed?term=25566131
Parent Title (English):Frontiers in psychology
Publisher:Frontiers Research Foundation
Place of publication:Lausanne
Document Type:Article
Language:English
Year of first Publication:2014
Year of Completion: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
Pagenumber:10
Organizational units:Humanwissenschaftliche Fakultät / Institut für Psychologie
Peer Review:Referiert
Publication Way:Open Access