Genetic Features of Dynamics of Heart Rate Variability at Work with Perspective Human — Computers Interfaces



The aim of the work was to assess the parameters of the heart rate variability of the user by the interfaces of the brain-computer, oculographic, respiratory, myographic, depending on the SNV in the genes that are somehow related to the functioning of the autonomic nervous system. Heart rate variability is an indicator of the cardiovascular system and a number of mechanisms regulating the whole organism, which can be used as one of the markers of the state of a human operator. The paper analyzes the association of point mutations of the HTR2A, APOE and TPH2 genes with HRV indices when users master a number of human-computer interfaces: brain-computer, oculographic, myographic and respiratory. The brain-computer interface is implemented on stable (well-established) visual evoked potentials; oculographic interface provided a set of text by eye movement, myographic provided the same task as the two above interfaces, due to changes in the user’s muscular activity; respiratory interface — due to changes in breathing. It has been shown that the SNV of the HTR2A and TPH2 genes involved in serotonin metabolism are associated with HRV indices in the development of neurocomputer interfaces. The SNV rs6313 HTR2A C allele carriers are characterized by higher rates of tonic effects on HRV when working with the oculographic interface, which is probably associated with an increase in serotonin receptor expression, which is involved in the vegetative regulation of heart rhythm. The genotype T / T SNV rs4290270 of the TPH2 gene is associated with a large spread of cardiointervals. This is probably due to an increase in the expression of the TPH2 gene, which catalyzes the limiting step of serotonin synthesis.

General Information

Keywords: heart rate variability, polymorphism, HTR2A, TPH2, serotonin, autonomic nervous system, human-computer interface

Journal rubric: Psychophysiology


Funding. The reported study was funded by Russian Foundation for Basic Research (RFBR), project number 17-29-02505 ofi_m.

For citation: Turovskiy Y.A., Gureev A.P., Vitkalova I.Y., Popov V.N., Vakhtin A.A. Genetic Features of Dynamics of Heart Rate Variability at Work with Perspective Human — Computers Interfaces. Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2021. Vol. 14, no. 1, pp. 172–186. DOI: 10.17759/exppsy.2021140108. (In Russ., аbstr. in Engl.)


  1. Babunts I.V., Mirizhanyan E.M., Mashahah Yu.A. The ABC of Heart Rate Variability Analysis. Stavropol. 2002. p. 109. (in Russ.).
  2. Baevsky R.M. Analysis of heart rate variability in space medicine. Human Physiology. 28 (2). P. 70—82. (in Russ.).
  3. Glantz S. Biomedical statistics. M.: Practice. 1998. P. 459. (in Russ.).
  4. Kulaichev A.P. Computer electrophysiology and functional diagnostics. Ed. 4th, pererabot. and add. M.: INFRA-M, 2007: p. 640. (in Russ.).
  5. Runion R. Handbook of nonparametric statistics. Modern approach. Translation from English E.Z. Demidenko. M.: Finance and Statistics. 1982. 198 p. (in Russ.).
  6. Ryabykina G.V., Sobolev A.V. Heart rate variability. M.: STARCO. 1998: 200 c. (in Russ.).
  7. Turovsky Ya.A., Kurgalin S.D., Alekseev A.V. Analysis of the movement of human eyes in the management of self-propelled chassis using a video-cusographic interface system. Sensory Systems. 2017; 31 (1): 51—58 s. (in Russ.).
  8. Alenina N., Kikic D., Todiras M., Mosienko V., Qadri F., Plehm R., Boye P., Vilianovitch L., Sohr R., Tenner K., Hörtnagl H., Bader M. Growth retardation and altered autonomic control in mice lacking brain serotonin. Proc Natl Acad Sci U S A. 2009. 106 (25).
  9. Chen G.L., Miller G.M. Tryptophan hydroxylase-2: an emerging therapeutic target for stress disorders. Biochem Pharmacol. 2013. 85 (9).
  10. Comet M.A., Bernard J.F., Hamon M., Laguzzi R., Sévoz-Couche C. Activation of the nucleus tractus solitarius 5-HT2A but not other 5-HT2 recep-tor subtypes inhibits the sympathetic activity in rats. Eur J Neurosci. 2007. 26 (2). P. 345—354.
  11. Heart rate variability Standards of measurement, physiological interpretation, and clinical use. European Heart Journal. 1996. 17 (3). P. 354—381.
  12. Jordan D. Vagal control of the heart: central serotonergic (5-HT) mechanisms. Exp Physiol. 2005. 90 (1). P. 175—181.
  13. Lotte F., Congedo M., Lécuyer A., Lamarche F., Arnaldi B. A EEG-based brain — computer interfaces. Journ. Neural Eng. 2007. 4 (2): R1 — R13.
  14. Martin P., Waters N., Schmidt C.J., Carlsson A., Carlsson M.L. Rodent data and general hypothesis: antipsychotic action exerted through 5-Ht2A receptor antagonism is increased by increased serotonergic tone. J Neural Transm (Vienna). 1998. 105 (4—5). P. 365—396.
  15. Martin W.C. Upper Limb Prostheses: A Review of the Literature with Hands on Hands. Evidence-Based Practice Group. 2011. P. 90.
  16. McFarland D.J., Wolpaw J.R. Brain — computer interfaces for communication and control. Commun ACM. 2011. 54 (5). P. 60—66.
  17. Puglielli L., Tanzi R.E., Kovacs D.M. Alzheimer’s disease: the cholesterol connection. Nat Neurosci. 2003. 6 (4). P. 345—351.
  18. Ren C., Baccarelli A., Wilker E., Suh H., Sparrow D., Vokonas P., Wright R., Schwartz J. Lipid and endothelium-related genes, ambient particulate matter, and heart rate variability — the VA Normative Aging Study. J Epi-demiol Community Health. 2010. 64 (1). P. 49—56.
  19. Schächinger, H., Weinbacher, M., Kiss A, Ritz R., Langewitz, W. Cardiovascular Indices of Peripheral and Central Sympathetic Activation. Psychosomatic Medicine. 2001. 63 (5). P. 788—796.
  20. Smith R.M., Papp A.C., Webb A., Ruble C.L., Munsie L.M., Nisenbaum L.K., Kleinman J.E., Lipska B.K., Sadee W. Multiple regulatory modulation expression of human cortex. Biol Psychiatry. 2013. 73 (6). P. 546—554.
  21. Turovsky Y.A., Gureev A.P., Vitkalova I.Yu., Popov V.N. Connection between polymorphisms in HTR2A, TPH2, BDNF, TOMM40 genes and the successful mastering of human—computer interfaces. J Genet. 2019. 98. P. 93.
  22. Zhang Y., Guo D., Xu P., Yao D. Robust frequency response for SSVEP-based BCI with temporally local multivariate synchronization index. Cogn Neurodyn. 2016. 10 (6). P. 505—511.

Information About the Authors

Yaroslav A. Turovskiy, PhD in Medicine, Associate Professor, Head of the Laboratory of Medical Cybernetics, Digital Technologies Department, Voronezh State University, Voronezh, Russia, ORCID:, e-mail:

Artyom P. Gureev, Assistant, Department of Genetics, Cytology and Bioengineering, Voronezh State University (FSBEI HE, Voronezh State University), Voronezh, Russia, ORCID:, e-mail:

Inna Y. Vitkalova, Postgraduate Student, Department of Biochemistry and Biotechnology, Voronezh State University of Engineering Technologies (Voronezh State University, Laboratory Assistant, Department of Genetics, Cytology and Bioengineering Voronezh State University (Voronezh State University), ORCID:, e-mail:

Vasily N. Popov, Rector, Voronezh State University of Engineering Technologies (Voronezh State University), Head of the Department of Genetics, Cytology and Bioengineering Voronezh State University (Voronezh State University), Voronezh, Russia, ORCID:, e-mail:

Aleksey A. Vakhtin, PhD in Physics and Matematics, Associate Professor, Department of Program¬ming and Information Technology, Faculty of Computer Science, Voronezh State University, Voronezh, Russia, ORCID:, e-mail:



Total: 459
Previous month: 9
Current month: 0


Total: 153
Previous month: 6
Current month: 1