Morphological inverse divergence reveals enhanced visual-attention structural similarity in internet gaming disorder

The morphometric inverse divergence (MIND) method offers a reliable approach for constructing structural similarity networks. While studies have identified abnormal connectivity in functional networks in internet gaming disorder (IGD), its MIND network pattern alterations remain unclear.

We analyzed 110 IGD individuals and 158 recreational gaming users (RGU), constructing MIND-based networks. We compared mean differences across large-scale sub-networks and individual regions. We also conducted edge analysis to identify subtle changes in individual connections. Additionally, we examined topological properties, including small-worldness, efficiency, and nodal centrality.

Individuals with IGD exhibited increased similarity between the visual and ventral attention/salience networks (Five significant edges), which was positively correlated with IGD severity. Additionally, several strengthened connections were identified, involving the default-sensorimotor and default-visual networks. Network topology analysis revealed a significant reduction in normalized characteristic path length in IGD (t = 2.357, p = 0.019), which may indicate a shift towards a more randomized brain network topology. Further, nodal centrality was also elevated (p < 0.001, uncorrected) in the same regions, including the visual, attentional, and prefrontal regions, showing a positive association with IGD severity.

Our findings revealed that excessive online gaming alters increased the similarity between the visual and attention network and increases nodal centrality in these regions, offering new insights into the neuroanatomical mechanisms underlying IGD.