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dc.contributor.author
Schad, Daniel J.
dc.contributor.author
Jünger, Elisabeth
dc.contributor.author
Sebold, Miriam
dc.contributor.author
Garbusow, Maria
dc.contributor.author
Bernhardt, Nadine
dc.contributor.author
Javadi, Amir-Homayoun
dc.contributor.author
Zimmermann, Ulrich S.
dc.contributor.author
Smolka, Michael N.
dc.contributor.author
Heinz, Andreas
dc.contributor.author
Rapp, Michael A.
dc.contributor.author
Huys, Quentin J.M.
dc.date.accessioned
2018-03-14T17:24:09Z
dc.date.available
2017-06-11T15:35:31Z
dc.date.available
2017-11-30T14:20:19Z
dc.date.available
2018-03-14T17:24:09Z
dc.date.issued
2014-12
dc.identifier.issn
1664-1078
dc.identifier.other
10.3389/fpsyg.2014.01450
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/96646
dc.identifier.doi
10.3929/ethz-b-000096646
dc.description.abstract
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 neuropsychiatric diseases associated with malfunctions of valuation.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Frontiers
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Decision-making
en_US
dc.subject
Reward
en_US
dc.subject
Cognitive abilities
en_US
dc.subject
Model-based and model-free learning
en_US
dc.subject
Fluid intelligence
en_US
dc.subject
Habitual and goal-directed system
en_US
dc.title
Processing speed enhances model-based over model-free reinforcement learning in the presence of high working memory functioning
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2014-12-17
ethz.journal.title
Frontiers in Psychology
ethz.journal.volume
5
en_US
ethz.journal.abbreviated
Front Psychol
ethz.pages.start
1450
en_US
ethz.size
10 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.publication.place
Lausanne
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02631 - Institut für Biomedizinische Technik / Institute for Biomedical Engineering::03955 - Stephan, Klaas E. / Stephan, Klaas E.
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02631 - Institut für Biomedizinische Technik / Institute for Biomedical Engineering::03955 - Stephan, Klaas E. / Stephan, Klaas E.
ethz.date.deposited
2017-06-11T15:35:51Z
ethz.source
ECIT
ethz.identifier.importid
imp593652d46476419908
ethz.ecitpid
pub:151328
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-13T17:28:26Z
ethz.rosetta.lastUpdated
2018-11-06T15:52:59Z
ethz.rosetta.versionExported
true
ethz.COinS
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