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

Author:

Kwon Mina1ORCID,Choi Hangnyoung23ORCID,Park Harhim1ORCID,Ahn Woo-Young145ORCID,Jung Young-Chul236ORCID

Affiliation:

1. Department of Psychology, Seoul National University, Seoul, South Korea

2. Department of Psychiatry, Yonsei University College of Medicine, Seoul, South Korea

3. Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea

4. Department of Brain and Cognitive Sciences, Seoul National University, Seoul, South Korea

5. AI Institute, Seoul National University, Seoul, South Korea

6. Institute for Innovation in Digital Healthcare, Yonsei University, Seoul, South Korea

Abstract

AbstractBackgroundAn 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).MethodParticipants diagnosed with IGD (n = 22) and AUD (n = 22), and healthy controls (n = 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.ResultsThe 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 ConclusionsThe 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.

Funder

Korea Health Technology R&D Project through the Korea Health Industry Development Institute

Ministry of Health & Welfare, Republic of Korea

Ministry of Science, Information and Communication Technologies and Future Planning, the Korean Government

Artificial Intelligence Graduate School Program

Publisher

Akademiai Kiado Zrt.

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