Revealing True and False Brain States Based on Wavelet Analysis of Electroencephalogram

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.

Ictal-interictal continuum:a review of recent advancements

Continuous electroencephalogram(cEEG)has become an indispensable technique in the management of critically ill patients for early detection and treatment of non-convulsive seizures(NCS)and non-convulsive status epilepticus(NCSE).It has also brought about a renaissance in a wide range of rhythmic and periodic patterns with heterogeneous frequency and morphology.These patterns share the rhythmic and sharp appearances of electrographic seizures,but often lack the necessary frequency,spatiotemporal evolution and clinical accompaniments to meet the definitive criteria for ictal patterns.They may be associated with cerebral metabolic crisis and neuronal injury,therefore not clearly interictal either,but lie along an intervening spectrum referred to as ictal-interictal continuum(IIC).Generally speaking,rhythmic and periodic patterns are categorized as interictal patterns when occurring at a rate of<1Hz,and are categorized as NCS and NCSE when occurring at a rate of>2.5 Hz with spatiotemporal evolution.As such,IIC commonly includes the rhythmic and periodic patterns occurring at a rate of 1–2.5 Hz without spatiotemporal evolution and clinical correlates.Currently there are no evidence-based guidelines on when and if to treat patients with IIC patterns,and particularly how aggressively to treat,presenting a challenging electrophysiological and clinical conundrum.In practice,a diagnostic trial with preferably a non-sedative anti-seizure medication(ASM)can be considered with the end point being both clinical and electrographic improvement.When available and necessary,correlation of IIC with biomarkers of neuronal injury,such as neuronal specific enolase(NSE),neuroimaging,depth electrode recording,cerebral microdialysis and oxygen measurement,can be assessed for the consideration of ASM treatment.Here we review the recent advancements in their clinical significance,risk stratification and treatment algorithm.