Neural underpinnings of internet gaming addiction tendency: The role of the limbic network in reward/punishment sensitivity and risky decision‐making alterations

Abstract Background and aims Internet gaming addiction (IGA) is associated with altered reward/punishment sensitivity and risky decision‐making. Nevertheless, the underlying neural mechanisms of such changes remain poorly understood. This study examined behavioral and neural predictors of IGA tendency with multiple datasets. Design Observational study. Setting and participants A total of 1142 university students [360 males and 782 females, mean (standard deviation) age of 18.75 (1.67) years] participated in the behavior‐brain cross‐sectional dataset (BBC). A subset of 303 BBC participants [71 males and 232 females, baseline mean age of 18.84 (1.72) years] participated in the behavior longitudinal dataset (BL). Measurements The Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) assessed sensitivity to reward and punishment stimuli. The Internet Game Addiction Questionnaire assessed levels of addiction symptoms in the context of internet games. The Iowa Gambling Task (IGT) assessed risky decision‐making behavior. Resting‐state functional magnetic resonance imaging (MRI) data were preprocessed using standard pipelines and analyzed based on Yeo's seven‐network parcellation template, with particular focus on the Limbic Network (LN) and its functional connectivity patterns. Statistical analyses included Spearman correlation, structural equation modeling and cross‐lagged panel models. Findings Cross‐sectional analyses revealed that the IGT net score (NS) was negatively associated with reward sensitivity (RS, rho = −0.181, P = 0.022), which was positively associated with punishment sensitivity (PS, rho = 0.125, P < 0.001). PS positively predicted IGA tendency (β = 0.180, P < 0.001). Additionally, LN strength exhibited a positive correlation with RS (rho = 0.077, P < 0.001) and a negative correlation with PS (rho = −0.045, P = 0.090). Moreover, the functional connectivity strength between LN and other functional networks was positively associated with RS. Longitudinal analyses demonstrated that (1) the IGT net score at the first time point (T1) negatively predicted RS at the second time point (T2, β = −0.123, P = 0.031), (2) RS at T1 positively predicted IGA tendency at T2 (β = 0.100, P = 0.019), (3) PS at T1 negatively predicted RS at T2 (β = 0.085, P = 0.056) and (4) LN strength at T1 directly predicted RS and PS at T1 (RS: β = 0.126, P = 0.027; PS: β = −0.104, P = 0.064), as well as RS at T2 (β = 0.079, P = 0.080). Conclusion Internet gaming activity net score appears to be negatively correlated with reward sensitivity. Punishment sensitivity appears to be positively correlated with tendency toward internet gaming activity. There appears to be a positive correlation between reward sensitivity and punishment sensitivity.