A trans-therapeutic signature of recovery in internet gaming disorder: From shared network reorganization to molecular underpinnings.
Zeng N, Fu J, Li S, Ni H, Li Q, Luo X et al. · Journal of behavioral addictions · 2026
Background and aims: A variety of self-regulation interventions have shown efficacy in treating Internet Gaming Disorder (IGD), but their shared and unique neurobiological mechanisms remain unclear. This study
Aims: to identify a common, trans-therapeutic neural signature of recovery and to delineate the specific connectivity fingerprints of five different self-regulation interventions for IGD.
Methods: This secondary analysis pooled resting-state fMRI data from 269 individuals with IGD who participated in one of five randomized controlled trials of self-regulation-based interventions: Approach Bias Modification (ApBM), Retrieval-Aversive Conditioning (R-AC), Progressive Aerobic Training (PAT), face-to-face Mindfulness Meditation (MM), and a Digital (online) mindfulness intervention. Participants were diagnosed with IGD according to DSM-5. Partial Least Squares (PLS) regression was used to identify a shared connectivity pattern associated with clinical improvement and similarity network fusion to define intervention-specific connectivity fingerprints. Imaging-transcriptomic analysis was further used to explore the molecular correlates.
Results: All interventions were associated with significant reductions in IGD severity. PLS analysis identified a shared connectivity pattern predictive of treatment response, characterized by a rebalancing of Subcortical Network (SCN) connectivity along the sensorimotor-association axis. This shared pattern was linked to gene expression profiles related to cellular stress and neuroplasticity. Each intervention also induced a unique connectivity fingerprint, targeting distinct neural circuits.
Discussion: and
Conclusions: Diverse self-regulation interventions for IGD converge on a shared therapeutic pathway involving the large-scale reorganization of cortico-subcortical circuits. These
Findings: identify a robust neurobiological phenotype of recovery, offering a potential biomarker for treatment response and a target for future circuit-based therapies.