Computer vision syndrome: neuro- and pathophysiological aspects (analytical review)
DOI: 10.32364/2311-7729-2024-24-1-6
R.R. Akhmadeev1,2, T.R. Mukhamadeev1, E.R. Shammasova2
1Bashkir State Medical University, Ufa, Russian Federation
2All-Russian Center for Eye and Plastic Surgery of the Bashkir State Medical University, Ufa, Russian Federation
The importance of studying the pathogenesis of computer vision syndrome (CVS) is due to the ever-increasing number of users of digital information technologies (DITs) and visual dis-play devices (VDDs) who work with them for long periods of the day. Most studies have classi-cally focused on epidemiological and etiological aspects of CVS. This article analyses 9 national and 42 international studies on CVS with a focus on its pathogenesis. The pathophysiological aspects of dry eye syndrome and accommodative dysfunction as the main branches of CVS in DIT and VDD users are discussed in the light of the morphological and functional unity of visual functions. The role of psychological status in the development and progression of refractive errors due to abnormalities in serotonin and dopamine metabolism is emphasized. Classical and recently published data on the possible role of sensory and visual-motor integration of the two main visual analyzer information channels (dorsal and ventral) in the development of CVS are discussed. A hypothesis based on the literature data and the results of our own research on the disintegration of visual and visual-motor processes in the development of CVS as a result of excessive, uncontrolled use of VDDs is hypothesized based on published data and the author's results.
Keywords: computer vision syndrome, dry eye disease, accommodation, pathogenesis, neurophysiology, visual motor integration.
For citation: Akhmadeev R.R., Mukhamadeev T.R., Shammasova E.R. Computer vision syndrome: neuro- and pathophysiological aspects (analytical review). Russian Journal of Clinical Ophthalmology. 2024;24(1):30–35 (in Russ.). DOI: 10.32364/2311-7729-2024-24-1-6.
About the authors:Rustem R. Akhmadeev — Dr. Sc. (Med.), Professor, professor of the Department of Psychiatry, Narcology, and Psychotherapy, Bashkir State Medical University; 3, Lenin str., Ufa, 450008, Russian Federation; medical psychologist of All-Russian Center for Eye and Plastic Surgery of the Bashkir State Medical University; 67/1, Zorge str., Ufa, 450075, Russian Federation; ORCID iD 0000-0002-0212-2162.
Timur R. Mukhamadeev — Dr. Sc. (Med.), Head of the Department of Ophthalmology with the course of the Institute of Additional Professional Education, Bashkir State Medical University; 3, Lenin str., Ufa, 450008, Russian Federation; ORCID iD 0000-0003-3078-2464.
Elmira R. Shammasova — C. Sc. (Med.), Head of the Organizational and Methodological Department, All-Russian Center for Eye and Plastic Surgery of the Bashkir State Medical University; 67/1, Zorge str., Ufa, 450075, Russian Federation; ORCID iD 0009-0007-1819-3241.
Contact information: Rustem R. Akhmadeev, e-mail: ahmadeevr@yandex.ru.
Financial Disclosure: no authors have a financial or property interest in any material or method mentioned.
There is no conflict of interest.
Received 27.12.2023.
Revised 18.01.2024.
Accepted 24.01.2024.
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14. Al-Mohtaseb Z., Schachter S., Lee B.S. et al. The relationship between dry eye disease and digital screen use. Clin Ophthalmol. 2021;15:3811–3820. DOI: 10.2147/OPTH.S321591.
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16. Moon J.H., Lee M.Y., Moon N.J. Association between video display terminal use and dry eye disease in school children. J Pediatr Ophthalmol Strabismus. 2014;51(2):87–92. DOI: 10.3928/01913913-20140128-01.
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18. Dartt D.A. Neural regulation of lacrimal gland secretory processes: relevance in dry eye diseases. Prog Retin Eye Res. 2009;28(3):155–177. DOI: 10.1016/j.preteyeres.2009.04.003.
19. Lee J.W., Cho H.G., Moon B.Y. et al. Effects of prolonged continuous computer gaming on physical and ocular symptoms and binocular vision functions in young healthy individuals. Peer J. 2019;4(7):e7050. DOI: 10.7717/peerj.7050.
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22. Hynes N.J., Cufflin M.P., Hampson K.M. et al. The effect of image resolution of display types on accommodative microfluctuations. Ophthalmic Physiol Opt. 2022;42(3):514–525. DOI: 10.1111/opo.12949.
23. Zhang M., Tang L.P., Ke H.Q. et al. Investigation on mental health of freshmen with myopia in a university in Guangdong Province. Chinese Journal of School Doctor. 2015;29:414–415,417.
24. Liu X.L., Li L.N., Yuan J. Personality characteristics and psychological status of high school students with myopia. Chinese General Practice. 2012;15:3194–3195,3200.
25. Yokoi T., Moriyama M., Hayashi K. et al. Predictive factors for comorbid psychiatric disorders and their impact on vision-related quality of life in patients with high myopia. Int Ophthalmol. 2014;34(2):171–183. DOI: 10.1007/s10792-013-9805-8.
26. Guo L.Y., Sun H., Hu M. et al. Mental health status of parents of young patients with high myopia. J Int Med Res. 2020;48(1):0300060519873474. DOI: 10.1177/0300060519873474.
27. Ko C.H., Yen J.Y., Liu S.C. et al. The associations between aggressive behaviors and internet addiction and online activities in adolescents. J Adolesc Health. 2009;44:598–605. DOI: 10.1016/j.jadohealth.2008.11.011.
28. Hong S.B., Zalesky A., Cocchi L. et al. Decreased functional brain connectivity in adolescents with internet addiction. PLoS One. 2013;8(2):e57831. DOI: 10.1371/journal.pone.0057831.
29. Hong S.B., Kim J.W., Choi E.J. et al. Reduced orbitofrontal cortical thickness in male adolescents with internet addiction. Behav Brain Funct. 2013;9:11. DOI: 10.1186/1744-9081-9-11.
30. Ho R.C., Zhang M.W., Tsang T.Y. et al. The association between internet addiction and psychiatric co-morbidity: a meta-analysis. BMC Psychiatry. 2014;14:183. DOI: 10.1186/1471-244X-14-183.
31. Potenza M.N. The Oxford handbook of digital technologies and mental health. New York: Oxford University Press; 2020.
32. Yuan K., Qin W., Liu Y., Tian J. Internet addiction: neuroimaging findings. Commun Integr Biol. 2011;4(6):637–639. DOI: 10.4161/cib.17871.
33. Dong G., DeVito E., Huang J., Du X. Diffusion tensor imaging reveals thalamus and posterior cingulate cortex abnormalities in internet gaming addicts. J Psychiatr Res. 2012;46(9):1212–1216. DOI: 10.1016/j. jpsychires.2012.05.015.
34. Norton D.J., McBain R.K., Pizzagalli D.A. et al. Dysregulation of visual motion inhibition in major depression. Psychiatry Res. 2016;240:214–221. DOI: 10.1016/j.psychres.2016.04.028.
35. Lin F., Zhou Y., Du Y. et al. Abnormal white matter integrity in adolescents with internet addiction disorder: a tract-based spatial statistics study. PLoS One. 2012;7:e30253. DOI: 10.1371/journal.pone.0030253.
36. Li S., Wu Q., Tang C. et al. Exercise-based interventions for internet addiction: neurobiological and neuropsychological evidence. Front Psychol. 2020;11:1296. DOI: 10.3389/fpsyg.2020.01296.
37. Yuan K., Cheng P., Dong T. et al. Cortical thickness abnormalities in late adolescence with online gaming addiction. PLoS One. 2013;8:e53055. DOI: 10.1371/journal.pone.0078708.
38. Zhu Y., Zhang H., Tian M. Molecular and functional imaging of internet addiction. Biomed Res Int. 2015;2015:378675. DOI: 10.1155/2015/378675.
39. Velichkovsky B.M., Korosteleva A.N., Pannasch S. et al. Two visual systems and their eye movements: a fixation-based event-related experiment with ultrafast fMRI reconciles competing views. Sovremennye tehnologii v medicine. 2019;11(4):7–16. DOI: 10.17691/stm2019.11.4.01.
40. Charman W.N., Heron G. Microfluctuations in accommodation: an upd ate on their characteristics and possible role. Ophthalmic Physiol Opt. 2015;35(5):476–499. DOI: 10.1111/opo.12234.
41. Milner A.D. How do the two visual streams interact with each other? Exp Brain Res. 2017;235(5):1297–1308. DOI: 10.1007/s00221-017-4917-4.
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