Using a Phenomenological Mathematical Model to Reproduce the Interaction of Endogenous and Exogenous Oscillations under Neurocontrol
The aim of the study was to evaluate the possibility of using a phenomenological mathematical model of the thalamocortical unit cell to describe the frequency-time responses of the real thalamocortical system (namely, various alpha rhythm modulations) and reproduce the signal dynamics in the process of neurobiocontrol.
Materials and Methods. The experimental part of this study (the resonant neurobiocontrol with double feedback based on the BioFeedBack2 software-hardware complex) was carried out according to the hybrid protocol: background — before/after: 2-minute record of the baseline vertex EEG (the active electrode — Cz grounding and the reference electrodes held on the earlobes); frequency scan during 210 s: exposure to pulsed infrared radiation with an increasing rate of from 8 to 14 Hz (frequency step — 0.1 Hz, time step — 3 s) and a music-like sound signal, the tone and volume of which determined by the peak amplitude in the spectrum of the current EEG in the range of 8–14 Hz. The characteristic feedback time is 10 ms, the frequency accuracy is 0.2–0.4 Hz. Periodic noise pulses, presented with a frequency related to the baseline heart rate, have been added to the sound signal.
For the calculations, a previously developed phenomenological model of the thalamocortical unit cell was used. The model incorporates interacting modules simulating the major neuronal modules of the brain, i.e., the thalamus, the cortex and the thalamic reticular nuclei.
Results and Discussion. Using the proposed phenomenological mathematical model of the thalamocortical unit cell, we obtained frequency-time responses of the model signal, which reproduces the frequency pattern of the real EEG signal. The model simulates the situation when the baseline alpha rhythm changes in response to an external factor with the known thalamocortical parameters. In the future, this information will improve the current feedback procedures of biocontrol aimed at enhancing the cognitive power of the brain. Appropriate training will allow controlling the alpha rhythm frequency (neurobiolcontrol) in such a way that, by the objective psychophysical criteria, the subjects will have their cognitive activity enhanced, and, by the subjective assessment, their well-being will improve.
Conclusion. In this study, a neuro-informational approach to personalized brain rhythm management is demonstrated. It is now possible to reproduce individual features of a complex information processing system using the proposed phenomenological model of the thalamocortical unit cell.
- Fedotchev A.I., Oh Sang Joon, Bondar’ A.T., Semenov V.S. Sovremennye vozmozhnosti i podkhody k aktivizatsii kognitivnoy deyatel’nosti i protsessov obucheniya u cheloveka [Current resources and approaches to activization of cognitive activity and learning processes in humans]. Pushchino: IBK RAN; 2017.
- Hammond D.C. What is neurofeedback: an update. J Neurother 2011; 15(4): 305–336, https://doi.org/10.1080/10874208.2011.623090.
- Miranda R.A., Casebeer W.D., Hein A.M., Judy J.W., Krotkov E.P., Laabs T.L., Manzo J.E., Pankratz K.G., Pratt G.A., Sanchez J.C., Weber D.J., Wheeler T.L., Ling G.S. DARPA-funded efforts in the development of novel brain–computer interface technologies. J Neurosci Methods 2015; 244: 52–67, https://doi.org/10.1016/j.jneumeth.2014.07.019.
- Fedotchev А.I., Parin S.B., Polevaya S.A., Velikova S.D. Brain-computer interface and neurofeedback technologies: current state, problems and clinical prospects (review). Sovremennye tehnologii v medicine 2017; 9(1): 175, https://doi.org/10.17691/stm2017.9.1.22.
- Fedotchev A.I., Bondar’ A.T., Bakhchina A.V., Parin S.B., Polevaya S.A., Radchenko G.S. Music-acoustic signals controlled by subject’s brain potentials in the correction of unfavorable functional states. Uspekhi fiziologicheskikh nauk 2016; 47(1): 69–79.
- Coulter D.A. Thalamocortical anatomy and physiology. In: Engel J. Jr., Pedley T.A. (editors). Epilepsy: a comprehensive textbook. Philadelphia: Lippincott Williams & Wilkins; 2007; p. 353–366.
- Kolosov A.V., Nuidel I.V., Yakhno V.G. Research of dynamic modes in the mathematical model of elementary thalamocortical cell. Izvestiya vysshikh uchebnykh zavedeniy. Prikladnaya nelineynaya dinamika 2016; 24(5): 72–83, https://doi.org/10.18500/0869-6632-2016-24-5-72-83.
- Bondar A., Shubina L. Nonlinear reactions of limbic structure electrical activity in response to rhythmical photostimulation in guinea pigs. Brain Res Bull 2018; 143: 73–82, https://doi.org/10.1016/j.brainresbull.2018.10.002.
- Fedotchev A.I., Bondar A.T., Bakhchina A.V., Grigorieva V.N., Katayev A.A., Parin S.B., Radchenko G.S., Polevaya S.A. Transformation of patient’s EEG oscillators into music-like signals for correction of stress-induced functional states. Sovremennye tehnologii v medicine 2016; 8(1): 93–98, https://doi.org/10.17691/stm2016.8.1.12.
