000890479 001__ 890479
000890479 005__ 20220228143453.0
000890479 0247_ $$2doi$$a10.3389/fnins.2020.536596
000890479 0247_ $$2ISSN$$a1662-453X
000890479 0247_ $$2ISSN$$a1662-4548
000890479 0247_ $$2Handle$$a2128/27138
000890479 0247_ $$2altmetric$$aaltmetric:97893837
000890479 0247_ $$2pmid$$a33536865
000890479 0247_ $$2WOS$$aWOS:000613265600001
000890479 037__ $$aFZJ-2021-00989
000890479 041__ $$aEnglish
000890479 082__ $$a610
000890479 1001_ $$0P:(DE-Juel1)137076$$aOberwelland Weiss, E.$$b0$$eCorresponding author
000890479 245__ $$aDevelopmental Differences in Probabilistic Reversal Learning: A Computational Modeling Approach
000890479 260__ $$aLausanne$$bFrontiers Research Foundation$$c2021
000890479 3367_ $$2DRIVER$$aarticle
000890479 3367_ $$2DataCite$$aOutput Types/Journal article
000890479 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1646041653_5297
000890479 3367_ $$2BibTeX$$aARTICLE
000890479 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000890479 3367_ $$00$$2EndNote$$aJournal Article
000890479 520__ $$aCognitive flexibility helps us to navigate through our ever-changing environment and has often been examined by reversal learning paradigms. Performance in reversal learning can be modeled using computational modeling which allows for the specification of biologically plausible models to infer psychological mechanisms. Although such models are increasingly used in cognitive neuroscience, developmental approaches are still scarce. Additionally, though most reversal learning paradigms have a comparable design regarding timing and feedback contingencies, the type of feedback differs substantially between studies. The present study used hierarchical Gaussian filter modeling to investigate cognitive flexibility in reversal learning in children and adolescents and the effect of various feedback types. The results demonstrate that children make more overall errors and regressive errors (when a previously learned response rule is chosen instead of the new correct response after the initial shift to the new correct target), but less perseverative errors (when a previously learned response set continues to be used despite a reversal) adolescents. Analyses of the extracted model parameters of the winning model revealed that children seem to use new and conflicting information less readily than adolescents to update their stimulus-reward associations. Furthermore, more subclinical rigidity in everyday life (parent-ratings) is related to less explorative choice behavior during the probabilistic reversal learning task. Taken together, this study provides first-time data on the development of the underlying processes of cognitive flexibility using computational modeling.
000890479 536__ $$0G:(DE-HGF)POF4-525$$a525 - Decoding Brain Organization and Dysfunction (POF4-525)$$cPOF4-525$$fPOF IV$$x0
000890479 536__ $$0G:(DE-HGF)POF4-5251$$a5251 - Multilevel Brain Organization and Variability (POF4-525)$$cPOF4-525$$fPOF IV$$x1
000890479 588__ $$aDataset connected to CrossRef
000890479 7001_ $$0P:(DE-Juel1)187098$$aKruppa, Jana$$b1
000890479 7001_ $$0P:(DE-Juel1)131720$$aFink, Gereon R.$$b2
000890479 7001_ $$0P:(DE-HGF)0$$aHerpertz-Dahlmann, Beate$$b3
000890479 7001_ $$0P:(DE-Juel1)174172$$aKonrad, Kerstin$$b4
000890479 7001_ $$0P:(DE-Juel1)131741$$aSchulte-Rüther, Martin$$b5
000890479 773__ $$0PERI:(DE-600)2411902-7$$a10.3389/fnins.2020.536596$$gVol. 14, p. 536596$$p536596$$tFrontiers in neuroscience$$v14$$x1662-453X$$y2021
000890479 8564_ $$uhttps://juser.fz-juelich.de/record/890479/files/Oberwelland%20Weiss_2021_FrontNeurosci_Developmental%20Differences%20in%20Probabilistic....pdf$$yOpenAccess
000890479 909CO $$ooai:juser.fz-juelich.de:890479$$pdnbdelivery$$popenaire$$pdriver$$pVDB$$popen_access
000890479 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2020-08-26
000890479 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000890479 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000890479 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bFRONT NEUROSCI-SWITZ : 2018$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Blind peer review$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central$$d2020-08-26
000890479 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2020-08-26
000890479 9141_ $$y2021
000890479 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)137076$$aForschungszentrum Jülich$$b0$$kFZJ
000890479 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)187098$$aForschungszentrum Jülich$$b1$$kFZJ
000890479 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131720$$aForschungszentrum Jülich$$b2$$kFZJ
000890479 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)174172$$aForschungszentrum Jülich$$b4$$kFZJ
000890479 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131741$$aForschungszentrum Jülich$$b5$$kFZJ
000890479 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0
000890479 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5251$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x1
000890479 9130_ $$0G:(DE-HGF)POF3-572$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$v(Dys-)function and Plasticity$$x0
000890479 920__ $$lyes
000890479 9201_ $$0I:(DE-Juel1)INM-3-20090406$$kINM-3$$lKognitive Neurowissenschaften$$x0
000890479 9201_ $$0I:(DE-Juel1)INM-11-20170113$$kINM-11$$lJara-Institut Quantum Information$$x1
000890479 980__ $$ajournal
000890479 980__ $$aVDB
000890479 980__ $$aI:(DE-Juel1)INM-3-20090406
000890479 980__ $$aI:(DE-Juel1)INM-11-20170113
000890479 980__ $$aUNRESTRICTED
000890479 9801_ $$aFullTexts