DOI:
https://doi.org/10.31071/kit2014.11.02

Inventory reference

ISSN 1812-7231 Klin.inform.telemed. Volume 10, Issue 11, 2014, Pages 21–31

Author(s)

K. G. Mazhirina^{1, 3}, M. V. Rezakova², M. A. Pokrovskiy^{1, 3}, A. A. Savelov², M. B. Shtark^{1, 3}

Institution(s)

¹Research Institute for Molecular Biology and Biophysics, SB RAMS, Novosibirsk, Russia ²Research Instititue "International Tomographic Centre", SB RAMS, Novosibirsk, Russia ³Company "Biofeedback Computer Systems", Novosibirsk, Russia

Article title

Central self-regulation mechanisms: fMRI study

Abstract (resume)

Introduction. The brain was mapped on-line using fMRI technology in the process of the development of self-regulation skills, controlled physiological characteristics.

Purpose. In this paper we present the results of the fMRI study of intracerebral dynamics of self-regulation skills development.

Results and discussion. The dynamics of new neural networks leave a trail of activity zones in the Middle Occipital Gyrus, Middle Temporal Gyrus, Middle Frontal Gyrus, Inferior Parietal Lobule and Declive, that are functionally related to cognitive actions and operations. We discuss the qualitative characteristics of the real and the imitation game periods. If one attempts to make a temporal "road map" of the real cognitive control of a virtual competitive game, the sequence of brain structures involvement is as follows: initially the extensive cortical fields are involved, then the area of the cuneus and the precuneus, and only after that the cognitive route reaches the cerebellum.

Conclusion. Summing up the discussion on the use of real feedback or its imitation, it should be noted that the effects of media training are not necessarily only limited to an increase or decrease of the RR interval length, and as a result, the acquisition of self-regulation skill. In the context of the study, the concept of perfecting may be possibly more informative, which correlates not only with the category of the game's aim (learning to reduce the heart rate), but also with the category of means (methods and strategies of self-control), allowing one to reach a goal. Indeed, if the same result can be achieved with less exertion of the body's regulatory systems, with greater confidence and flexibility, such as in the case of real feedback, it is reasonable to accept these characteristics of a completed task as signs of improvement.

Keywords

Self-regulation, Functional magnetic resonance tomography, Biofeedback technology, Neuroimaging, Cognitive and personality characteristics

References

1. Boldyreva G. N., Zhavoronkova L. A., Sharov E. V. et al. EEG-fMRI study of healthy human brain responses to functional loads. Fiziologiya cheloveka [Human Physiology], 2009, vol. 35, iss. 3, pp. 20–30. (In Russ.).

2. Boldyreva G. N., Zhavoronkova L. A., Sharov E. V. et al. EEG-fMRI analysis of the functional specialization of the human brain in normal and cerebral pathology. Meditsinskaya vizualizatsiya [Medical Imaging], 2012, iss. 1, pp. 15–25. (In Russ.).

3. Mazhirina K. G. Personality characteristics and dynamics of self-regulation during game control: thesis for PhD in psychology, Novosibirsk, 2009. (In Russ.).

4. Mazhirina K. G., Pokrovsky M. A., Rezakova M. V., Savelov A. A., Savelova O. A., Shtark M. B. Neuroimaging of the dynamics of real and simulated biofeedback in-line of functional magnetic resonance imaging. Byulleten eksperimentalnoy biologii i meditsiny [The Bulletin of Experimental Biology and Medicine], 2012, vol. 154, iss. 12, pp. 664–669. (In Russ.).

5. Rezakova M. V., Mazhirina K. G., Pokrovsky M. A., Savelov A. A., Savelova O. A., Shtark M. B. Dynamic mapping of the brain and cognitive control of a virtual game (research by using functional magnetic resonance imaging). Byulleten eksperimentalnoy biologii i meditsiny [The Bulletin of Experimental Biology and Medicine], 2012, vol. 154, iss. 12, pp. 669–674. (In Russ.).

6. Rezakova M. V., Mazhirina K. G., Pokrovsky M. A., Savelov A. A., Savelova O. A., Shtark M. B. Functional magnetic resonance imaging in the study of dynamic brain mapping and cognitive control of a virtual game. Byulleten sibirskoy meditsiny [The Bulletin of Siberian Medicine], 2012, iss. 5 (addendum), pp. 105–107. (In Russ.).

7. Chernikova L. A., Ioffe M. E., Busheneva S. N. et al. Electromyographic biofeedback and functional magnetic resonance imaging in post-stroke rehabilitation (demonsrated in the learning of precision grasp). Byulleten sibirskoy meditsiny [The Bulletin of Siberian Medicine], 2010, iss. 2, pp. 12–16. (In Russ.).

8. Ushakov V. L., Verhlyutov V. M., Sokolov P. A. et al. Activation of the brain structures on fMRI data when viewing movies or recalling demonstrated actions. Zhurnal vysshey nervnoy deyatelnosti [Journal of Higher Nervous Activity], 2011, vol. 61, iss. 5, pp. 553–565. (In Russ.).

9. Schnaider N. A., Shilov S. N., Shtark M. B. et al. Techniques of functional magnetic resonance imaging used in the diagnosis of attention deficit and hyperactivity disorder. Funktsionalnaya diagnostika [Functional diagnostics], 2007, iss. 2, pp. 75–81, 2007, iss. 3, pp. 86–90. (In Russ.).

10. Shtark M. B., Korostishevskaya A. M., Rezakova M. V., Savelov A. A. Functional magnetic resonance imaging and neuroscience. Uspehi fiziologicheskih nauk [Successes of Physiological Sciences], 2012, vol. 43, iss. 1, pp. 3–29. (In Russ.).

11. Endepols H., Sommer S., Backes H., J. Effort-based decision making in the rat: an [18F] fluorodeoxyglucose micro positron emission tomography study. The J. of Neuroscience, 2010, vol. 30, iss. 29, pp. 9708–9714.
https://doi.org/10.1523/JNEUROSCI.1202-10.2010
PMid:20660253

12. Hook J. On the role of the cerebellum and basal ganglia in cognitive singnal processin. Progr. Brain Res., 1997, vol. 114, pp. 543–552.
https://doi.org/10.1016/S0079-6123(08)63385-3

13. Joaquim R., Phillips Mary L., Russell T., Lawrence N. et al. Neural response to specific components of fearful faces in healthy and schizophrenic adults. NeuroImage, 2010, vol. 49, iss. 1, pp. 939–946.

14. Laufs H. Endogenous brain oscillations and related networks detected by surface EEG-combined fMRI. Hum. Brain Mapp., 2008, vol. 29, pp. 762–769.
https://doi.org/10.1002/hbm.20600
PMid:18465797

15. McCarthy G., Puce A., Gore J. C. Allison T. Face-specific processing in the human fusiform gyrus. J. Cognitive Neuroscicence, 1997, iss. 9, pp. 605–610.

16. Ogawa S., Lee T., Nayak A. S., Glynn P. Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magn. Reson. Med., 1990, vol. 14, iss. 1, pp. 68–78.
https://doi.org/10.1002/mrm.1910140108
PMid:2161986

17. Oshin V., Vinod G., Elaine L., Fisher M., Granic J. Middle Temporal Gyrus Encodes Individual Differences in Perceived Facial Attractiveness. Psychology of Aesthetics, Creativity, and the Arts, 2013, vol. 7, iss. 1, pp. 38–47. doi: 10.1037/a0031591.
https://doi.org/10.1037/a0031591

18. Reeber S. L., Otis T. S., Sillitoe R. V. New roles for the cerebellum in health and disease. Front Syst Neurosci., 2013, vol. 14, iss. 7, p. 83. doi: 10.3389/fnsys.2013.00083.
https://doi.org/10.3389/fnsys.2013.00083

19. Talairach J. Co-Planar Stereotactic Atlas of the Human Brain. Thieme Medical Publ., New York, 1988.
PMid:3129671

20. Tavano A., Borgatti R. Evidence for a link among cognition, language and emotion in cerebellar malformations. Cortex, 2010, vol. 46, iss. 7, pp. 907–18.
https://doi.org/10.1016/j.cortex.2009.07.017
PMid:19857864

21. Мazhirina К, Rezakova M, Mark B. Shtark. Neuroimaging phenomenology of the sentral self-regulation mechanisms. J. of Behavioral and Brain Science, 2014, iss. 4, pp. 58–68.

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