Gaming Addiction Transmission: Interpersonal Neural Pathways Revealed by HYPER-NESS

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Authors: Chuyang Sun, Mattia Rosso, Ruoyu Niu, Xinyu Ye, Tinghao Tang, Peter Vuust, Leonardo Bonetti, Rixin Tang
Cited by: 1
References: 62

Abstract

Abstract Gaming addiction may be contagious through social interaction. In team competitive video games, individuals of varying addiction levels are often paired. This raises the question of whether, and through what mechanisms, one individual’s addiction level is affected by other players. Methodologically, addressing this question requires understanding both what happens between brains and within individual brains during a gaming session. To this end, we used HYPER-NESS (Hyper Brain Network Estimation via Source Separation), a novel analytical framework to decompose and weight the distinct contributions of inter-brain and intra-brain processes to social brain networks. We applied this framework to a hyperscanning fNIRS dataset where dyads were scanned while playing a video game together against experimenters. We found that inter-brain and intra-brain contributions to the social brain networks were differentially associated with changes in game reward and social reward sensitivity, depending on the addiction level of one’s partner. Granger causality analysis of both social and individual brain networks revealed influences from the high-addiction partner to low-addiction partner. Furthermore, significant cross-frequency coupling was found selectively between low-addiction players, supporting the idea that this form of inter-brain interactions underpins the joint processing of task-relevant rewards. To our knowledge, these findings provide the first neural-level account for the hypothesis that gaming addiction propagates though dyadic social interaction.

Fields of Study & Subjects

Neural and Behavioral Psychology Studies Functional Brain Connectivity Studies Impact of Technology on Adolescents

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
23 June 2026
Document type
Preprint