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Neural correlates of model-based behavior in internet gaming disorder and alcohol use disorder

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dc.contributor.author정영철-
dc.contributor.author최항녕-
dc.date.accessioned2024-05-23T03:26:57Z-
dc.date.available2024-05-23T03:26:57Z-
dc.date.issued2024-03-
dc.identifier.issn2062-5871-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/199224-
dc.description.abstractAn imbalance between model-based and model-free decision-making systems is a common feature in addictive disorders. However, little is known about whether similar decision-making deficits appear in internet gaming disorder (IGD). This study compared neurocognitive features associated with model-based and model-free systems in IGD and alcohol use disorder (AUD). Method: Participants diagnosed with IGD (n 5 22) and AUD (n 5 22), and healthy controls (n 5 30) performed the two-stage task inside the functional magnetic resonance imaging (fMRI) scanner. We used computational modeling and hierarchical Bayesian analysis to provide a mechanistic account of their choice behavior. Then, we performed a model-based fMRI analysis and functional connectivity analysis to identify neural correlates of the decision-making processes in each group. Results: The computational modeling results showed similar levels of model-based behavior in the IGD and AUD groups. However, we observed distinct neural correlates of the model-based reward prediction error (RPE) between the two groups. The IGD group exhibited insula-specific activation associated with model-based RPE, while the AUD group showed prefrontal activation, particularly in the orbitofrontal cortex and superior frontal gyrus. Furthermore, individuals with IGD demonstrated hyper-connectivity between the insula and brain regions in the salience network in the context of model-based RPE. Discussion and Conclusions: The findings suggest potential differences in the neurobiological mechanisms underlying model-based behavior in IGD and AUD, albeit shared cognitive features observed in computational modeling analysis. As the first neuroimaging study to compare IGD and AUD in terms of the model-based system, this study provides novel insights into distinct decision-making processes in IGD.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherAkadémiai Kiadó-
dc.relation.isPartOfJOURNAL OF BEHAVIORAL ADDICTIONS-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAlcoholism*-
dc.subject.MESHBayes Theorem-
dc.subject.MESHBehavior, Addictive*-
dc.subject.MESHBrain-
dc.subject.MESHBrain Mapping-
dc.subject.MESHHumans-
dc.subject.MESHInternet-
dc.subject.MESHInternet Addiction Disorder-
dc.subject.MESHMagnetic Resonance Imaging-
dc.subject.MESHVideo Games*-
dc.titleNeural correlates of model-based behavior in internet gaming disorder and alcohol use disorder-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Psychiatry (정신과학교실)-
dc.contributor.googleauthorMina Kwon-
dc.contributor.googleauthorHangnyoung Choi-
dc.contributor.googleauthorHarhim Park-
dc.contributor.googleauthorWoo-Young Ahn-
dc.contributor.googleauthorYoung-Chul Jung-
dc.identifier.doi10.1556/2006.2024.00006-
dc.contributor.localIdA03656-
dc.contributor.localIdA06480-
dc.relation.journalcodeJ03353-
dc.identifier.eissn2063-5303-
dc.identifier.pmid38460004-
dc.subject.keywordalcohol use disorder-
dc.subject.keywordcomputational modeling-
dc.subject.keywordinternet gaming disorder-
dc.subject.keywordmodel-based behavior-
dc.subject.keywordsalience network-
dc.contributor.alternativeNameJung, Young Chul-
dc.contributor.affiliatedAuthor정영철-
dc.contributor.affiliatedAuthor최항녕-
dc.citation.volume13-
dc.citation.number1-
dc.citation.startPage236-
dc.citation.endPage249-
dc.identifier.bibliographicCitationJOURNAL OF BEHAVIORAL ADDICTIONS, Vol.13(1) : 236-249, 2024-03-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Psychiatry (정신과학교실) > 1. Journal Papers

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