E.A. Yumatov¹, N.A. Karatygin², E.N. Dudnik³, A.E. Khramov4, V.V. Grubov5, S.S. Pertsov6

1,2,6 P.K. Anokhin Research Institute of Normal Physiology (Moscow, Russia) 

4,5 Innopolis University (Innopolis, Russia) 

6 I.M. Sechenov First Moscow State Medical University (Moscow, Russia)

It is a well-known fact that mental activity of the brain can be presented by two different states, i.e., the true state and the false state. A promising method of the electroencephalogram (EEG) wavelet transform has been developed over recent years. Using this method, we evaluated the principle possibility for direct objective registration of mental activity in the human brain.

Previously we developed and described (published) a new experimental model and software for recognizing the true and false mental responses of a person with the EEG wavelet transform.

The developed experimental model and software-and-data support allowed us to compare (by EEG parameters) two mental states of brain activity, one of which is the false state, while another is the true state.

The goal of this study is to develop an absolutely new information technology for recognizing the true and false states in mental activity of the brain by means of the EEG wavelet transform.

Our study showed that the true and false states of the brain can be distinguished using the method of continuous wavelet transform and calculation of the EEG wavelet energy. It was revealed that the main differences between truthful and false mental responses are observed in the delta and alpha ranges of the EEG. In the EEG delta rhythm, the wavelet energy is much higher under conditions of the false response as compared to that in the true response. In the EEG alpha rhythm, the wavelet energy is significantly higher with the true answer than in the false one.

These data open a new principal possibility of revealing the true and false mental state of the brain by means of continuous wavelet transform and calculation of the EEG wavelet energy.

Yumatov E.A., Karatygin N.A., Dudnik E.N., Khramov A.E., Grubov V.V., Pertsov S.S. Recognition of true and false states of the brain by means of the electroencephalogram wavelet analysis. Biomedicine Radioengineering. 2021. V. 24. № 1. P. 5–12. DOI: 10.18127/j15604136-202101-01 (In R

1. Holodnyj Yu.I. Analiz fiziologiCheskih reakcij, registriruemyh v processe oprosa s is-pol'zovaniem poligrafa: Prakt. posobie. M. 1999.  S. 6–52 (In Russian). 
2. Ogloblin S.I., Molchanov A.Yu. Instrumental'naYa «detekciYa lZhi»: akademiCheskij kurs. Yaroslavl': NYuans. 2004. 464 s. (In Russian).
3. Zhurin S.I. Praktika i teoriYa ispol'zovaniYa detektorov lZhi. Izd. 2-e, stereotip. M.: Go-rYaChaYa liniYa – Telekom. 2011. 144 s. (In Russian).
4. Pavlov I.P. Dvadcatiletnij opyt ob"ektivnogo izuCheniYa vysShej nervnoj deYatel'nosti (povedeniYa) Zhivotnyh. PSS. M.–L.: Izd. AN SSSR. 1951 (In Russian).
5. Anohin P.K. Psihicheskaya forma otraZheniYa dejstvitel'nosti. V sb.: LeninskaYa teoriYa ot-raZheniYa i sovremennost'. Pod red.  T. Pavlova. 1969. SofiYa. Razd. 1. Gl 3. S. 109 (In Russian).
6. Bekhtereva N.P., Budzen P.V., Gogolicyn Yu.L. Mozgovye kody psihiCheskoj deYatel'nosti. L.: Nauka. 1977. 165 s. (In Russian).
7. Ivanickij A.M. GlavnaYa zagadka prirody: kak na osnove processov mozga voznikaYut sub"-ektivnye pereZhivaniYa. PsihologiCheskij Zhurnal. 1999. T. 20. № 3. S. 93–104 (In Russian).
8. Nagel' T. Myslimost' nevozmoZhnogo i problema duha i tela. Voprosy filosofii. 2001. № 10. S. 92–107 (In Russian).
9. Sudakov K.V. Sistemnye mekhanizmy psihiCheskoj deYatel'nosti. NevrologiYa i psihiatriYa im. S.S. Korsakova. 2010. T. 110. № 2.  S. 4–14 (In Russian).
10. Popper K. Znanie i psihofiziCheskaYa problema: v zaShChitu vzaimodejstviYa: Per. s angl. I.V. Zhuravleva. M. 2008. 256 c. (In Russian).
11. Crick F., Koch C. Why neuroscience may be able to explain consiousness. Scientific Amer. 1995. V. 273. P. 66.
12. Sperry R.W. Neurology and the mind-brain problem. Am. Sci. 1952. V. 40. P. 291–312. 
13. Yumatov E.A. PsihiCheskaYa deYatel'nost' mozga – «klYuCh» k poznaniYu. Vestnik MeZhduna-rodnoj akademii nauk. RusskaYa sekciYa. 2013. № 1. S. 35–45 (In Russian).
14. Yumatov E.A. To knowledge of the origin of the brain mental activity. World Journal of Neuro-science 2014. V. 4. № 2. P. 170–18213. 
15. Yumatov E.A. Distancionno-polevye proYavleniYa psihiCheskoj deYatel'nosti mozga. Bio-medicinskaYa radioelektronika. 2019. T. 22. 
16. Yumatov E.A. The molecularly fielding psyChophysical nature of the brain mental activity. J. Neuroscience and Medicine. 2019. V.10. № 2. P. 55–74.
17. Grubov V.V., Sitnikova E.Yu., Koronovskij A.A., Pavlov A.N., Hramov A.E. AvtomatiChe-skoe vydelenie i analiz oscillYatornyh patternov na nestacionarnyh signalah EEG s ispol'zo-vaniem vejvletnogo preobrazovaniYa i metoda empiriCheskih mod. Izv. RAN. Ser. FiziCheskaYa. 2012. № 76(12). S. 1520–1523 (In Russian).
18. Koronovskij A.A., Makarov V.A., Pavlov A.N., Sitnikova E.Yu., Hramov A.E. Vejvlety v nejrodinamike i nejrofiziologii. M.: Fizmatlit. 2013 (In Russian).
19. Pavlov A.N., Hramov A.E., Koronovskij A.A., Sitnikova E.Yu., Makarov V.A., OvChinnikov A.A. Vejvlet-analiz v nejrodinamike. UFN. 2012. № 182(9). C. 905–939 (In Russian).
20. Hramov A.E., Koronovskii A.A., Makarov V.A., Pavlov A.N., Sitnikova E.Yu. Wavelets in Neuro-science. Springer Heidelberg New York DordreCht London. 2015. 318 p. 
21. Yumatov E.A., Hramov A.E., Grubov V.V., GlazaChev O.S, Dudnik E.N., Karatygin N.A. Is-sledovanie vozmoZhnosti raspoznavaniYa psihiCheskoj deYatel'nosti mozga na osnove vejvletnogo analiza elektroencefalogrammy. BiomedicinskaYa radioelektronika. 2018. № 4. S. 3–12 (In Russian).
22. Yumatov E.A., Hramov A.E., Grubov V.V., GlazaChev O.S., Dudnik E.N., Karatygin N.A. Possi-bility for recognition of psyChic brain activity with continuous wavelet analysis of EEG. Journal of Be-havioral and Brain Science (JBBS). 2019. V. 9. № 3. P. 67–77.
23. Yumatov E.A., Potapov V.Yu., Karatygin N.A., Percov S.S. Eksperimental'naYa model' i programmnoe obespeChenie dlYa raspoznaniYa pravdivyh i loZhnyh myslennyh otvetov na osnove analiza elektroencefalogrammy. BiomedicinskaYa radioelektronika. 2019. T. 22.  № 5. S. 38–44 (In Russian). 
24. Yumatov E.A., Potapov V.Yu., Karatygin N.A., Dudnik E.N., Pertsov S.S. Experimental approaCh to the recognition of truthful and false mental responses based on the wavelet transform of the electroen-cephalogram. J. Trends in Med. 2019. V. 4. № 19.
25. Miller Jr. R. G. Beyond ANOVA: basics of applied statistics. CRC press. 1997.
26. Chan Y.H. Biostatistics 102: quantitative data–parametric & non-parametric tests. Blood Press. 2003. V. 140. № 24.08. P. 79.