Hangnyoung Choi

clinical assistant professor

Yonsei University College of Medicine
Country flagSouth Korea

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About

Hangnyoung Choi is a Clinical Assistant Professor at Yonsei University College of Medicine in South Korea. His research focuses on various aspects of neurodevelopmental disorders, including autism spectrum disorder and attention-deficit/hyperactivity disorder, utilizing advanced machine learning techniques for risk stratification and diagnostic tools. Additionally, he investigates the neural correlates associated with behavioral disorders such as internet gaming disorder and alcohol use disorder.

Articles (9)

Year:

2025

Year:

2025

Background An 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 = 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. 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.

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2020

Collaborators (2)

Young-Chul Jung

Yonsei University College of Medicine

SOUTH KOREA
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Ryemi Do

Research Professor

Seoul National University Hospital

SOUTH KOREA
View details
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