Random topology organization and decreased visual processing of internet addiction: Evidence from a minimum spanning...

Area of Science:

• Neuroscience
• Brain Network Analysis
• Electroencephalography (EEG)

Background:

• Internet addiction (IA) is linked to brain alterations, but functional connectivity (FC) and network changes remain unclear.
• Previous studies show inconsistent results regarding IA's impact on brain networks.

Purpose of the Study:

• To investigate functional and topological brain network alterations in college students with IA using electroencephalography (EEG).
• To analyze changes in network hubs and overall network organization in individuals with IA.

Main Methods:

• Utilized Young's Internet Addiction Test for severity assessment.
• Recorded EEG data from 30 IA and 30 healthy control (HC) participants.
• Applied Phase Lag Index (PLI) and Minimum Spanning Tree (MST) analysis to assess FC and network topology.

Main Results:

• IA participants exhibited higher delta FC in frontal and parieto-occipital regions.
• MST analysis revealed a more star-like network topology in IA individuals across alpha and beta bands.
• The occipital brain region showed reduced importance in IA participants, correlating with IA severity.

Conclusions:

• Functional brain networks in IA are characterized by increased FC and a more random organization.
• These findings suggest significant alterations in brain mechanisms underlying Internet addiction.
• The study highlights the importance of network analysis in understanding IA's neurological impact.