Brain network alterations in mobile phone use problem severity: A multimodal neuroimaging analysis

Abstract

[Background and aims] Problematic mobile phone use can disrupt social interaction and well-being, potentially influencing cognitive processes. This study investigated whether mobile phone use problem severity is associated with alterations in the topological organization of brain networks. [Methods] Rs-fMRI and DTI data were collected from 81 healthy participants. Graph theory analyses were applied. The Mobile Phone Problem Use Scale-10 (MPPUS-10) was used to assess mobile phone use problem severity. Correlation analyses were conducted between each graph metric and questionnaire scores. [Results] MPPUS-10 scores correlated with global fMRI metrics: higher scores linked to longer shortest path length (reduced integration) and lower global efficiency (reduced information transfer). Conversely, higher MPPUS-10 scores were correlated with a greater clustering coefficient and higher local efficiency, which reflect increased local connectivity. Furthermore, higher MPPUS-10 scores were associated with a higher sigma value from DTI, indicating altered structural network properties. Some specific brain regions also showed significant correlations with MPPUS-10 scores. [Discussion and conclusion] These findings indicate that higher mobile phone use problem severity is associated with decreased integration and increased segregation of functional networks, alongside enhanced small-worldness in structural networks. Reduced integration aligns with addiction theories suggesting digital overload worsens network dysfunction, disrupting brain connectivity. Additionally, higher severity was correlated with altered connectivity in multiple regions, such as the precentral gyrus, supplementary motor area, and postcentral gyrus. These regions are associated with motor control, sensorimotor processing, and memory function. Further research is needed to explore whether these findings reflect shifts in the integration and integrity of brain information-processing modules.