On the issue of the electroencephalographic phenomenon «burst-suppression»: variants of outcomes and possible neurophysiological mechanisms

Objective: to evaluate the indicators of electrical activity of the brain using frequency- spectral analysis and data of three- dimensional localization of sources of pathological activity for an approach to the analysis of possible neurophysiological mechanisms of the brain of patients whose EEG recorded the phenomenon of ‘burst- suppression’.Material and methods: 45 electroencephalograms recorded in 22 patients (average age 51.05; 11 women, 11 men) were analyzed. In 12 patients, the EEG study was performed in dynamics from 1 to 8 times. At the time of the first registration, the ‘burst- suppression’phenomenon was recorded in the EEG of all patients. The level of wakefulness of all patients, with the exception of patients who were under anesthesia, was 3 points on the Glasgow coma scale.EEG recording was performed on electroencephalographs ‘Encephalan- EEGR-19/26’, ‘Mitsar- EEG-10/70–201’, ‘Mitsar- EEG-SmartBCI’, ‘Neuron- Spectrum-5’and ‘Neuron- Spectrum-65’in accordance with the International scheme of arrangement of electrodes 10–20 %. A frequency- spectral analysis of the power of the ‘burst’and ‘suppression’periods was carried out — the fast Fourier transform method was used. The program ‘BrainLoc 6.1’(Russia) was used for localization of equivalent dipole sources of pathological electrical activity of the ‘burst’period.Results: during the first EEG recording, the ‘burst- suppression’phenomenon was recorded in all patients. In seven patients, the ‘burst’period in the ‘burstsuppression’phenomenon was visually represented by slow-wave oscillations, in 15 patients, the ‘burst’periods resembled epileptiform discharges. In frequency- spectral analysis EEG in all patients in the ‘burst’period, the dominance of the power of slow-wave oscillations (mainly in the delta range) was noted. According to the program ‘BrainLoc 6.1’, equivalent dipole sources of pathological activity of the ‘burst’period were recorded at the level of the thalamus, in the medio- basal parts of the frontal and temporal lobes on both sides. A favorable outcome of the ‘burst- suppression’phenomenon was observed in only five patients of 22, all other patients had an unfavorable outcome.Conclusion: a favorable outcome of the ‘burst- suppression’phenomenon was observed only in patients under sevorane anesthesia and in some patients after acute poisoning with drugs that affect the central nervous system, while patients after brain anoxia had an unfavorable outcome. In prognostic terms, our data are comparable to the literature data. The changes revealed during the frequency-spectral analysis of the EEG in the form of the dominance of the power of slow-wave oscillations (mainly in the delta range), as well as the localization of the supposed generators of electrical activity in the ‘burst’ period at the level of the thalamus, in the mediobasal parts of the frontal and temporal lobes (according to the ‘BrainLoc 6.1’program), may to some extent be consistent with the data of experimental works and mathematical models of the ‘burst–suppression’phenomenon If the ‘burst- suppression’ phenomenon is detected during EEG registration, it is advisableto conduct a dynamic EEG study or EEG monitoring.

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Electroencephalogram indices in patients undergoing cardiac arrest

Medical alphabet ◽

10.33667/2078-5631-2020-14-32-38 ◽

2020 ◽

Vol 1 (14) ◽

pp. 32-38

Author(s):

I. Yu. Berezina ◽

L. I. Sumsky ◽

A. Yu. Mikhailov ◽

Yu. L. Arzumanov

Keyword(s):

Cardiac Arrest ◽

Electrical Activity ◽

Paroxysmal Activity ◽

Equivalent Dipole ◽

Neurophysiological Mechanisms ◽

Eeg Changes ◽

Eeg Recordings ◽

The Moment ◽

Electroencephalogram Eeg ◽

The Brain

Objective: to assess the safety of indicators of electrical activity of the brain for the approach to the analysis of the basic neurophysiological mechanisms of the brain in patients after cardiac arrest.Materials and methods: 52 patients were examined (age — 54,68 ± 19,33) after cardiac arrest. At the time of recording the electroencephalogram (EEG), the level of wakefulness of the examined patients on the Glasgow coma scale was in the range of 3 to 13 points. In 35 patients, EEG recording was performed starting from the first three days from the moment of cardiac arrest, in 17 patients — from the fourth to the 18th day. EEG was registered on electroencephalographs ‘Encephalan–EEGR–19/26’ by ‘Medikom MTD’, ‘Neuron-Spectrum–5/EP’ and ‘Neuron-Spectrum–65’ by ‘Neurosoft’ in accordance with the recommendations of the International Federation of Clinical Neurophysiologists (IFCN). The duration of a single EEG recordings lasted at least 30 min. To localize equivalent dipole sources of pathological activity we used the program ‘BrainLoc 6.0’, (Russia). In 19 patients EEG was recorded in dynamics from 2 to 8 times.Results: all patients showed EEG changes of varying severity, which can be divided into three groups (according to the severity of changes in the EEG: moderate, severe and rough). In the group of patients with gross changes in EEG can be identified 4 variants: the first variant — absence of the alpha rhythm and the dominance of slow-wave fluctuations of the frequency spectrum; variant II — continuous generalized paroxysmal activity; variant III — phenomenon of ‘burst-suppression’; variant IV — a marked decrease in the amplitude of electrical activity of the brain to the level of 2–4 microvolt.Conclusions: based on the dynamics of the EEG pattern in patients after cardiac arrest, it is possible to assume with a certain degree of probability the level of violations in the basic mechanisms of the brain.

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NEUROPHYSIOLOGICAL MECHANISMS OF LOGONEUROSIS IN PRESCHOOL CHILDREN DURING FUNCTIONAL STRESS

Science and Education ◽

10.24195/2414-4665-2020-3-2 ◽

2020 ◽

Vol 2020 (3) ◽

pp. 13-19

Author(s):

Nataliia Vasylieva

Keyword(s):

Preschool Children ◽

Electrical Activity ◽

Spectral Power ◽

Low Frequency ◽

Bioelectrical Activity ◽

Subcortical Structures ◽

Zonal Distribution ◽

Neurophysiological Mechanisms ◽

The Brain ◽

Functional Stress

The changes in the electrical activity of the brain of boys with different tempo-rhythmic characteristics of speech during functional stress have been studied, namely, a series of flashes of light of a certain frequency – rhythmic photostimulation have been used. The bioelectrical activity of the brain has been studied using a computer electroencephalography system. Also, according to the methodology of zonal distribution of normalized spectral power (SP) of the rhythm of the main frequency of the EEGranges, the particles (in percent) of the normalized SP of electrogenesis in each of the four main ranges (δ, θ, α, β) have been determined. As a result of comparison of the light flashing frequency assimilation among boys in the studied groups, it has been found, that in the group of children with logoneurosis slow rhythms (5 Hz,) lying within the theta-range of the EEG, were better assimilated. The rhythm is assimilated in the low frequency range among the children with logoneurosis. The relative spectral power of theta-rhythm significantly decreased on the EEG of children with tempo and rhythm speech disorder at low-frequency photostimulation in comparison with the corresponding indicators of the background electroencephalogram; the corresponding indicators in the beta-range, anterior and posterior leads in the alpha-rangeincreased. Based on the obtained data, it has been found, that children with logoneurosis have insufficient response to photostimulation. Such data are associated with insufficient inhibitory effect of the cortex on the subcortical structures. The reduced reactivity and functional insufficiency of the activating system of the brain stem have been noted. Neurophysiological mechanisms of logoneurosis are due to the state of insufficient formation of brain structures, which is confirmed by the results of electroencephalography during rhythmic photostimulation. Changes in the tempo and rhythm of speech during logoneurosis of preschool children provoke stress of the brain mechanisms of regulation, which become apparent by special characteristics of the electrical activity of the brain, both at rest and during load.

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Instantaneous EEG Signal Analysis Based on Empirical Mode Decomposition Applied to Burst-Suppression in Propofol Anaesthesia

General Reanimatology ◽

10.15360/1813-9779-2021-5-65-79 ◽

2021 ◽

Vol 17 (5) ◽

pp. 65-79

Author(s):

G. Sobolova ◽

M. S. Fabus ◽

M. Fischer ◽

M. Drobny ◽

B. Drobna-Saniova

Keyword(s):

Spectral Analysis ◽

General Anaesthesia ◽

Empirical Mode Decomposition ◽

Brain Activity ◽

Low Frequency ◽

Burst Suppression ◽

Intrinsic Mode Functions ◽

Mode Decomposition ◽

Cyclic Changes ◽

The Brain

The human electroencephalogram (EEG) constitutes a nonstationary, nonlinear electrophysiological signal resulting from synchronous firing of neurons in thalamocortical structures of the brain. Due to the complexity of the brain's physiological structures and its rhythmic oscillations, analysis of EEG often utilises spectral analysis methods.Aim: to improve clinical monitoring of neurophysiological signals and to further explain basic principles of functional mechanisms in the brain during anaesthesia.Material and methods. In this paper we used Empirical Mode decomposition (EMD), a novel spectral analysis method especially suited for nonstationary and nonlinear signals. EMD and the related Hilbert-Huang Transform (HHT) decompose signal into constituent Intrinsic Mode Functions (IMFs). In this study we applied EMD to analyse burst-suppression (BS) in the human EEG during induction of general anaesthesia (GA) with propofol. BS is a state characterised by cyclic changes between significant depression of brain activity and hyper-active bursts with variable duration, amplitude, and waveform shape. BS arises after induction into deep general anaesthesia after an intravenous bolus of general anaesthetics. Here we studied the behaviour of BS using the burst-suppression ratio (BSR).Results. Comparing correlations between EEG and IMF BSRs, we determined BSR was driven mainly by alpha activity. BSRs for different spectral components (IMFs 1-4) showed differing rates of return to baseline after the end of BS in EEG, indicating BS might differentially impair neural generators of low-frequency EEG oscillations and thalamocortical functional connectivity.Conclusion. Studying BS using EMD represents a novel form of analysis with the potential to elucidate neurophysiological mechanisms of this state and its impact on post-operative patient prognosis.

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Fit Vs Faint: Assessing Work Causation in “Idiopathic Fall” Cases

Guides Newsletter ◽

10.1001/amaguidesnewsletters.2014.sepoct01 ◽

2014 ◽

Vol 19 (5) ◽

pp. 3-12

Author(s):

Lorne Direnfeld ◽

David B. Torrey ◽

Jim Black ◽

LuAnn Haley ◽

Christopher R. Brigham

Keyword(s):

Blood Flow ◽

Electrical Activity ◽

Loss Of Consciousness ◽

Brain Electrical Activity ◽

Medical Terminology ◽

Scientific Analysis ◽

Medical Causation ◽

The Individual ◽

The Brain ◽

Current Science

Abstract When an individual falls due to a nonwork-related episode of dizziness, hits their head and sustains injury, do workers’ compensation laws consider such injuries to be compensable? Bearing in mind that each state makes its own laws, the answer depends on what caused the loss of consciousness, and the second asks specifically what happened in the fall that caused the injury? The first question speaks to medical causation, which applies scientific analysis to determine the cause of the problem. The second question addresses legal causation: Under what factual circumstances are injuries of this type potentially covered under the law? Much nuance attends this analysis. The authors discuss idiopathic falls, which in this context means “unique to the individual” as opposed to “of unknown cause,” which is the familiar medical terminology. The article presents three detailed case studies that describe falls that had their genesis in episodes of loss of consciousness, followed by analyses by lawyer or judge authors who address the issue of compensability, including three scenarios from Arizona, California, and Pennsylvania. A medical (scientific) analysis must be thorough and must determine the facts regarding the fall and what occurred: Was the fall due to a fit (eg, a seizure with loss of consciousness attributable to anormal brain electrical activity) or a faint (eg, loss of consciousness attributable to a decrease in blood flow to the brain? The evaluator should be able to fully explain the basis for the conclusions, including references to current science.

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Anticonvulsant Effects of Carbonic Anhydrase Inhibitors: The Enigmatic Link Between Carbonic Anhydrases and Electrical Activity of the Brain

Neurochemical Research ◽

10.1007/s11064-021-03390-2 ◽

2021 ◽

Author(s):

Hatice Zehra Ozsoy

Keyword(s):

Carbonic Anhydrase ◽

Electrical Activity ◽

Carbonic Anhydrases ◽

Carbonic Anhydrase Inhibitors ◽

The Brain ◽

Anticonvulsant Effects

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The Electrical Activity of the Brain

Scientific American ◽

10.1038/scientificamerican0654-54 ◽

1954 ◽

Vol 190 (6) ◽

pp. 54-63 ◽

Cited By ~ 3

Author(s):

W. Grey Walter

Keyword(s):

Electrical Activity ◽

The Brain

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Identification of Brain Electrical Activity Related to Head Yaw Rotations

Sensors ◽

10.3390/s21103345 ◽

2021 ◽

Vol 21 (10) ◽

pp. 3345

Author(s):

Enrico Zero ◽

Chiara Bersani ◽

Roberto Sacile

Keyword(s):

Electrical Activity ◽

Electrical Stimulus ◽

Head Movements ◽

Brain Electrical Activity ◽

Output Function ◽

Input Output ◽

Eeg Signals ◽

Head Turning ◽

Identification Technique ◽

The Brain

Automatizing the identification of human brain stimuli during head movements could lead towards a significant step forward for human computer interaction (HCI), with important applications for severely impaired people and for robotics. In this paper, a neural network-based identification technique is presented to recognize, by EEG signals, the participant’s head yaw rotations when they are subjected to visual stimulus. The goal is to identify an input-output function between the brain electrical activity and the head movement triggered by switching on/off a light on the participant’s left/right hand side. This identification process is based on “Levenberg–Marquardt” backpropagation algorithm. The results obtained on ten participants, spanning more than two hours of experiments, show the ability of the proposed approach in identifying the brain electrical stimulus associate with head turning. A first analysis is computed to the EEG signals associated to each experiment for each participant. The accuracy of prediction is demonstrated by a significant correlation between training and test trials of the same file, which, in the best case, reaches value r = 0.98 with MSE = 0.02. In a second analysis, the input output function trained on the EEG signals of one participant is tested on the EEG signals by other participants. In this case, the low correlation coefficient values demonstrated that the classifier performances decreases when it is trained and tested on different subjects.

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