A multi-scale, circuit-to-gene signature of approach-bias modification in internet gaming disorder

Wang, Min and Fu, Jiejie and Li, Shuang and Wei, Meiting and Dong, Guang-Heng (2026) A multi-scale, circuit-to-gene signature of approach-bias modification in internet gaming disorder. JOURNAL OF BEHAVIORAL ADDICTIONS, 15 (2). pp. 787-797. ISSN 2062-5871

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Abstract

Background Approach-bias modification (ApBM) is a cognitive training intervention with potential therapeutic value for internet gaming disorder (IGD). However, its clinical efficacy and the underlying neural mechanisms remain to be systematically investigated. This study aimed to evaluate the effectiveness of ApBM for IGD and to identify the associated multi-scale neurobiological signatures, from brain connectivity to gene expression. Methods We conducted a randomized controlled trial involving individuals with IGD assigned to either an ApBM (N = 30) or a control group (N = 27). Resting-state functional magnetic resonance imaging data were collected pre- and post-intervention. We applied non-negative matrix factorization and a machine learning framework to identify intervention-related functional connectivity patterns. Imaging-transcriptomic analysis was then used to explore the molecular foundations of the identified neural signature. Results The ApBM intervention led to a reduction in IGD symptoms and craving. A specific functional connectivity pattern, characterized by anti-connectivity between the visual and ventral attention network (VAN), was identified via machine learning as a potential neural marker of the intervention. This pattern's statistical significance under conservative permutation test was (p = 0.06–0.08). It was spatially coupled to genes enriched in neurodevelopmental and synaptic transmission processes. Conclusions This study provides multi-scale evidence supporting ApBM as an intervention for IGD. The remodeling between vision and the VAN may reflect a mechanism that interrupts the automatic capture of attention by gaming cues, a process regulated by genes associated with neuroplasticity. We propose a circuit-to-gene framework for understanding ApBM in IGD, though the identified neural signature warrants further independent validation.

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