TITLE:
Revealing True and False Brain States Based on Wavelet Analysis of Electroencephalogram
AUTHORS:
Evgeny Antonovich Yumatov, Elena Nikolaevna Dudnik, Oleg Stanislavovich Glazachev, Anna Igorevna Filipchenko, Sergey Sergeevich Pertsov
KEYWORDS:
Information Technology, Electroencephalogram (EEG), Continuous EEG Wavelet Transformations, Mental Activity of the Brain, Consciousness, Truth and Falsehood
JOURNAL NAME:
Neuroscience and Medicine,
Vol.13 No.2,
June
16,
2022
ABSTRACT: Statement of the Problem: As you know, there exist two different states in the brain’s mental activity: true and false. In recent years, a progressive method of wavelet transformation of the electroencephalogram (EEG) has been developed, which enabled us to establish the fundamental possibility of direct objective registration of the human brain’s mental activity. Earlier, we created an experimental model and software for recognizing true and false mental responses of a person based on the EEG wavelet transformation and described it in the article. The developed experimental model and information software made it possible to compare the two mental states of brain activity by electroencephalographic indicators, one of which is false and the other is true. The goal is to develop a fundamentally new information technology for recognizing true and false states in the brain’s mental activity based on the wavelet transformation of the electroencephalogram. Results: It was revealed that the true and false states of the brain can be distinguished using the method of continuous wavelet transformation and calculation of the EEG wavelet energy. It is shown that the main differences between true and false mental responses are observed in the delta and alpha ranges of the EEG. In the EEG delta rhythm, the wavelet energy is reliably higher in case of a false answer compared to a true one. In the EEG alpha rhythm, the wavelet energy is significantly higher with a true answer than a false one. Practical significance of the research: The data obtained open up the fundamental possibility of identifying true and false mental states of the brain on the basis of continuous wavelet transformation and calculation of the EEG wavelet energy.