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. 2024 Feb 6;13(1):120-133.
doi: 10.1556/2006.2023.00077. Print 2024 Mar 26.

Negative emotions mediate the association between the topology of the complex brain network and smartphone use disorder: A resting-state EEG study

Yulong Yin  1 , Xu Li  1 , Joseph T F Lau  2   3   4 , Sunian Nan  1 , Mingkun Ouyang  5 , Xiao Cai  6 , Pengcheng Wang  7
Affiliations

Negative emotions mediate the association between the topology of the complex brain network and smartphone use disorder: A resting-state EEG study

Yulong Yin et al. J Behav Addict. .

Abstract

Background: Increasing research has examined the factors related to smartphone use disorder. However, limited research has explored its neural basis.

Aims: We aimed to examine the relationship between the topology of the resting-state electroencephalography (rs-EEG) brain network and smartphone use disorder using minimum spanning tree analysis. Furthermore, we examined how negative emotions mediate this relationship.

Methods: This study included 113 young, healthy adults (mean age = 20.87 years, 46.9% males).

Results: The results showed that the alpha- and delta-band kappas and delta-band leaf fraction were positively correlated with smartphone use disorder. In contrast, the alpha-band diameter was negatively correlated with smartphone use disorder. Negative emotions fully mediated the relationship between alpha-band kappa and alpha-band diameter and smartphone use disorder. Furthermore, negative emotions partially mediated the relationship between delta-band kappa and smartphone use disorder. The findings suggest that excessive scale-free alpha- and delta-band brain networks contribute to the emergence of smartphone use disorder. In addition, the findings also demonstrate that negative emotions and smartphone use disorder share the same neural basis. Negative emotions play a mediating role in the association between topological deviations and smartphone use disorder.

Discussion: To the best of our knowledge, this is the first study to examine the neural basis of smartphone use disorder from the perspective of the topology of the rs-EEG brain network. Therefore, neuromodulation may be a potential intervention for smartphone use disorder.

Keywords: minimum spanning tree; negative emotions; resting-state EEG; smartphone use disorder.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Schematic representation of the EEG complex brain network analysis. (a) Pre-processed EEG data; (b) Power spectra. Coloured boxes indicate the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands; (c) Functional connectivity matric; (d) Minimal span tree; and (e) Topology of the MST brain network
Fig. 2.
Fig. 2.
The mediation model. The association between alpha-band K and smartphone use disorder is fully mediated by negative emotions. All path coefficients are standard regression coefficients
Fig. 3.
Fig. 3.
The mediation model. The association between alpha-band D and smartphone use disorder is fully mediated by negative emotions. All path coefficients are standard regression coefficients
Fig. 4.
Fig. 4.
The mediation model. The association between delta-band K and smartphone use disorder is partially mediated by negative emotions. All path coefficients are standard regression coefficients
See this image and copyright information in PMC

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References

    1. Babiloni, C., Lopez, S., Noce, G., Ferri, R., Panerai, S., Catania, V., … Carducci, F. (2023). Relationship between default mode network and resting-state electroencephalographic alpha rhythms in cognitively unimpaired seniors and patients with dementia due to Alzheimer's disease. Cerebral Cortex, 33(20), 10514–10527. 10.1093/cercor/bhad300. - DOI - PMC - PubMed
    1. Balconi, M., Campanella, S., & Finocchiaro, R. (2017). Web addiction in the brain: Cortical oscillations, autonomic activity, and behavioral measures. Journal of Behavioral Addictions, 6(3), 334–344. 10.1556/2006.6.2017.041. - DOI - PMC - PubMed
    1. Ball, T. M., Squeglia, L. M., Tapert, S. F., & Paulus, M. P. (2020). Double dipping in machine learning: Problems and solutions. Biological Psychiatry Cognitive Neuroscience and Neuroimaging, 5(3), 261–263. 10.1016/j.bpsc.2019.09.003. - DOI - PMC - PubMed
    1. Barry, R. J., Clarke, A. R., Johnstone, S. J., Magee, C. A., & Rushby, J. A. (2007). EEG differences between eyes-closed and eyes-open resting conditions. Clinical Neurophysiology, 118(12), 276–2773. 10.1016/j.clinph.2007.07.028. - DOI - PubMed
    1. Bian, M., & Leung, L. (2014). Linking loneliness, shyness, smartphone addiction symptoms, and patterns of smartphone use to social capital. Social Science Computer Review, 33(1), 61–79. 10.1177/0894439314528779. - DOI

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