Features of bioelectric brain activity of 18–22 years old male students with internet addiction

BACKGROUND: Excessive use of the Internet for entertainment or aimless activities often results in the development of Internet addiction.

AIM: To study bioelectrical activity of the brain in young men aged 18–22 with Internet addiction using the EEG spectral analysis data. Specifically, the analysis will focus on the full spectrum power and rhythm indices.

METHODS: The study involved 61 volunteers who were students in their first or second year of full-time education at the University of Tyumen (UTMN). These volunteers were young men with an average age of 19.63±1.27 years and were residents of Tyumen and the Tyumen region. To categorize the participants, the Chen method (CIAS) was used to divide them into two groups: Internet addicts and a control group. A background EEG was recorded using 16 standard leads. A spectral analysis of the EEG was then conducted, focusing on the total power of the spectrum, the power of the spectrum in the alpha range (µV2), and the rhythm index. The groups were compared using Mann–Whitney U-test.

RESULTS: EEG Type 1 was found in 86% of individuals with addiction. This type exhibited an alpha rhythm structure that was well-organized in both time and space. Additionally, it displayed pronounced spindles. EEG Type 2 was observed in 14% of addicted students. It was characterized by hypersynchronous alpha activity, which was weakly modulated or not modulated into spindles. It also exhibited high Rhythm Index values. In the control group of young men, three types of normal EEG organization were identified. Most of the controls (69%) displayed an organized Type 1 pattern. Eight percent exhibited a hypersynchronous Type 2 pattern. The remaining 23% showed a desynchronous Type 3 pattern, which was characterized by a low representation of the alpha-component. Instead, theta- and beta1-rhythms were noted. When comparing the total power of the spectrum in the main frequency ranges (0.5–35 Hz), higher values were observed in the group of individuals addicted to the Internet, as compared to the control group. Specifically, the left anterior frontal Fp1 (U=210; Z=2.04; p=0.049), right parietal P4 (U=215; Z=2.07; p=0.049), right and left occipital O1 (U=180; Z=2.76; p=0.006), O2 (U=187; Z=2.64; p=0.008), left temporal T3 (U=230; Z=1.92; p=0.050), and left posterior temporal T5 (U=201; Z=2.41; p=0.015) leads exhibited significantly higher values.

CONCLUSION: The bioelectrical activity patterns of the brains of UTMN male students addicted to the Internet indicate a developed stage of the addictive process. During this stage, there are no significant negative EEG manifestations of Internet addiction. This can be attributed to the adaptive mechanisms that have developed in these individuals because of their lifestyle.