001031202 001__ 1031202 001031202 005__ 20251103202052.0 001031202 0247_ $$2doi$$a10.1007/s11065-024-09647-1 001031202 0247_ $$2ISSN$$a1040-7308 001031202 0247_ $$2ISSN$$a1573-6660 001031202 0247_ $$2datacite_doi$$a10.34734/FZJ-2024-05602 001031202 037__ $$aFZJ-2024-05602 001031202 082__ $$a610 001031202 1001_ $$0P:(DE-Juel1)131699$$aMüller, Veronika I.$$b0$$eCorresponding author 001031202 245__ $$aNot All Stroop-Type Tasks Are Alike: Assessing the Impact of Stimulus Material, Task Design, and Cognitive Demand via Meta-analyses Across Neuroimaging Studies 001031202 260__ $$aDordrecht [u.a.]$$bSpringer Science + Business Media B.V$$c2024 001031202 3367_ $$2DRIVER$$aarticle 001031202 3367_ $$2DataCite$$aOutput Types/Journal article 001031202 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1762162357_6331 001031202 3367_ $$2BibTeX$$aARTICLE 001031202 3367_ $$2ORCID$$aJOURNAL_ARTICLE 001031202 3367_ $$00$$2EndNote$$aJournal Article 001031202 520__ $$aThe Stroop effect is one of the most often studied examples of cognitive conflict processing. Over time, many variants of the classic Stroop task were used, including versions with different stimulus material, control conditions, presentation design, and combinations with additional cognitive demands. The neural and behavioral impact of this experimental variety, however, has never been systematically assessed. We used activation likelihood meta-analysis to summarize neuroimaging findings with Stroop-type tasks and to investigate whether involvement of the multiple-demand network (anterior insula, lateral frontal cortex, intraparietal sulcus, superior/inferior parietal lobules, midcingulate cortex, and pre-supplementary motor area) can be attributed to resolving some higher-order conflict that all of the tasks have in common, or if aspects that vary between task versions lead to specialization within this network. Across 133 neuroimaging experiments, incongruence processing in the color-word Stroop variant consistently recruited regions of the multiple-demand network, with modulation of spatial convergence by task variants. In addition, the neural patterns related to solving Stroop-like interference differed between versions of the task that use different stimulus material, with the only overlap between color-word, emotional picture-word, and other types of stimulus material in the posterior medial frontal cortex and right anterior insula. Follow-up analyses on behavior reported in these studies (in total 164 effect sizes) revealed only little impact of task variations on the mean effect size of reaction time. These results suggest qualitative processing differences among the family of Stroop variants, despite similar task difficulty levels, and should carefully be considered when planning or interpreting Stroop-type neuroimaging experiments.Keywords: Activation likelihood estimation; Cognitive control; Interference resolution; Neuroimaging meta-analysis; Stroop. 001031202 536__ $$0G:(DE-HGF)POF4-5251$$a5251 - Multilevel Brain Organization and Variability (POF4-525)$$cPOF4-525$$fPOF IV$$x0 001031202 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de 001031202 7001_ $$0P:(DE-Juel1)131855$$aCieslik, Edna C.$$b1 001031202 7001_ $$0P:(DE-HGF)0$$aFicco, Linda$$b2 001031202 7001_ $$0P:(DE-Juel1)186037$$aTyralla, Sandra$$b3 001031202 7001_ $$0P:(DE-HGF)0$$aSepehry, Amir Ali$$b4 001031202 7001_ $$0P:(DE-HGF)0$$aAziz-Safaie, Taraneh$$b5 001031202 7001_ $$0P:(DE-HGF)0$$aFeng, Chunliang$$b6 001031202 7001_ $$0P:(DE-Juel1)131678$$aEickhoff, Simon B.$$b7 001031202 7001_ $$0P:(DE-Juel1)131693$$aLangner, Robert$$b8 001031202 773__ $$0PERI:(DE-600)2018507-8$$a10.1007/s11065-024-09647-1$$p-$$tNeuropsychology review$$v-$$x1040-7308$$y2024 001031202 8564_ $$uhttps://juser.fz-juelich.de/record/1031202/files/s11065-024-09647-1.pdf$$yOpenAccess 001031202 8767_ $$d2025-01-06$$eHybrid-OA$$jDEAL 001031202 909CO $$ooai:juser.fz-juelich.de:1031202$$pdriver$$pOpenAPC_DEAL$$popen_access$$popenaire$$pdnbdelivery$$popenCost$$pVDB 001031202 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131699$$aForschungszentrum Jülich$$b0$$kFZJ 001031202 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131855$$aForschungszentrum Jülich$$b1$$kFZJ 001031202 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131678$$aForschungszentrum Jülich$$b7$$kFZJ 001031202 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131693$$aForschungszentrum Jülich$$b8$$kFZJ 001031202 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$$x0 001031202 915pc $$0PC:(DE-HGF)0000$$2APC$$aAPC keys set 001031202 915pc $$0PC:(DE-HGF)0001$$2APC$$aLocal Funding 001031202 915pc $$0PC:(DE-HGF)0002$$2APC$$aDFG OA Publikationskosten 001031202 915pc $$0PC:(DE-HGF)0113$$2APC$$aDEAL: Springer Nature 2020 001031202 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2023-08-25 001031202 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0 001031202 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bNEUROPSYCHOL REV : 2022$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)3002$$2StatID$$aDEAL Springer$$d2023-08-25$$wger 001031202 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess 001031202 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bNEUROPSYCHOL REV : 2022$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)1120$$2StatID$$aDBCoverage$$bBIOSIS Reviews Reports And Meetings$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)0130$$2StatID$$aDBCoverage$$bSocial Sciences Citation Index$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2023-08-25 001031202 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2023-08-25$$wger 001031202 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2023-08-25 001031202 920__ $$lyes 001031202 9201_ $$0I:(DE-Juel1)INM-7-20090406$$kINM-7$$lGehirn & Verhalten$$x0 001031202 980__ $$ajournal 001031202 980__ $$aVDB 001031202 980__ $$aUNRESTRICTED 001031202 980__ $$aI:(DE-Juel1)INM-7-20090406 001031202 980__ $$aAPC 001031202 9801_ $$aAPC 001031202 9801_ $$aFullTexts