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dc.contributor.author
Paliwal, Saee
dc.contributor.author
Petzschner, Frederike H.
dc.contributor.author
Schmitz, Anna K.
dc.contributor.author
Tittgemeyer, Marc
dc.contributor.author
Stephan, Klaas Enno
dc.date.accessioned
2018-08-31T14:57:18Z
dc.date.available
2017-06-11T11:02:44Z
dc.date.available
2018-08-31T14:57:18Z
dc.date.issued
2014-07
dc.identifier.other
10.3389/fnhum.2014.00428
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/86781
dc.identifier.doi
10.3929/ethz-b-000086781
dc.description.abstract
Impulsivity plays a key role in decision-making under uncertainty. It is a significant contributor to problem and pathological gambling (PG). Standard assessments of impulsivity by questionnaires, however, have various limitations, partly because impulsivity is a broad, multi-faceted concept. What remains unclear is which of these facets contribute to shaping gambling behavior. In the present study, we investigated impulsivity as expressed in a gambling setting by applying computational modeling to data from 47 healthy male volunteers who played a realistic, virtual slot-machine gambling task. Behaviorally, we found that impulsivity, as measured independently by the 11th revision of the Barratt Impulsiveness Scale (BIS-11), correlated significantly with an aggregate read-out of the following gambling responses: bet increases (BIs), machines switches (MS), casino switches (CS), and double-ups (DUs). Using model comparison, we compared a set of hierarchical Bayesian belief-updating models, i.e., the Hierarchical Gaussian Filter (HGF) and Rescorla–Wagner reinforcement learning (RL) models, with regard to how well they explained different aspects of the behavioral data. We then examined the construct validity of our winning models with multiple regression, relating subject-specific model parameter estimates to the individual BIS-11 total scores. In the most predictive model (a three-level HGF), the two free parameters encoded uncertainty-dependent mechanisms of belief updates and significantly explained BIS-11 variance across subjects. Furthermore, in this model, decision noise was a function of trial-wise uncertainty about winning probability. Collectively, our results provide a proof of concept that hierarchical Bayesian models can characterize the decision-making mechanisms linked to the impulsive traits of an individual. These novel indices of gambling mechanisms unmasked during actual play may be useful for online prevention measures for at-risk players and future assessments of PG.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Frontiers Research Foundation
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/3.0/
dc.subject
Hierarchical Gaussian Filter
en_US
dc.subject
Hierarchical Bayesian Model
en_US
dc.subject
Baratt Impulsiveness Scale
en_US
dc.subject
Impulsivity
en_US
dc.subject
Pathological gambling
en_US
dc.title
A Model-Based Analysis of Impulsivity Using a Slot-Machine Gambling Paradigm
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 3.0 Unported
dc.date.published
2014-07-03
ethz.journal.title
Frontiers in Human Neuroscience
ethz.journal.volume
8
en_US
ethz.pages.start
428
en_US
ethz.size
17p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.identifier.nebis
010194181
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
2017-06-11T11:05:36Z
ethz.source
ECIT
ethz.identifier.importid
imp5936521b0680e12905
ethz.ecitpid
pub:136567
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-12T18:20:04Z
ethz.rosetta.lastUpdated
2018-11-08T01:24:20Z
ethz.rosetta.versionExported
true
ethz.COinS
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