Age-related changes in electrical activity of the brain. Decoding EEG in children. Electroencephalogram of the brain - definition and essence of the method
Keywords
CHILDREN/TEENAGERS/ AGE DEVELOPMENT/ BRAIN / EEG / NORTH / ADAPTATION / CHILDREN / ADOLESCENTS / BRAIN DEVELOPMENT / EEG / THE NORTH / ADAPTATIONannotation scientific article on medical technologies, author of the scientific work - Soroko S.I., Rozhkov Vladimir Pavlovich, Bekshaev S.S.
Using an original method for assessing the structure of the interaction of EEG components (waves), the dynamics of the formation of patterns of bioelectric activity of the brain and age-related changes in the relationships between the main frequency components of the EEG, characterizing the features of the development of the central nervous system in children and adolescents living in the difficult environmental conditions of the North of the Russian Federation, were studied. It has been established that the statistical structure of the interaction of EEG components undergoes significant changes with age and has its own topographic and gender differences. In the period from 7 to 18 years, the probability of interaction of waves of all frequency ranges of EEG rhythms with waves of delta and theta ranges decreases, with a simultaneous increase in interaction with waves of beta and alpha2 ranges. To the greatest extent, the dynamics of the analyzed EEG indicators are manifested in the parietal, temporal and occipital areas of the cerebral cortex. The greatest gender differences in the analyzed EEG parameters occur during the puberty period. By the age of 16-17, in girls, the functional core of the interaction of wave components, which supports the structure of the EEG pattern, is formed in the alpha2-beta1 range, while in boys it is in the alpha2-alpha1 range. The severity of age-related changes in the EEG pattern reflects the gradual formation of electrogenesis of various brain structures and has individual characteristics determined by both genetic and environmental factors. The obtained quantitative indicators of the formation of dynamic relationships of the basic rhythms with age make it possible to identify children with impaired or delayed development of the central nervous system.
Related topics scientific works on medical technologies, author of the scientific work - Soroko S.I., Rozhkov Vladimir Pavlovich, Bekshaev S.S.
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Features of CNS development have been investigated in children and adolescents living under the severe ecological conditions in the North of Russia. The original method for estimating a time structure of the EEG frequency components interrelations was used to study the dynamics of maturation of bioelectrical brain activity pattern and age-related changes of the interplay between the main EEG rhythms. It was found that the statistical structure of the interaction of the frequency components of EEG is undergoing a significant restructuring with age and has certain topography and gender differences. The period from 7 to 18 years of age is marked by a decrease in the probability of interaction of wave components of the main EEG frequency bands with components of delta and theta bands while simultaneously increasing interaction with the components of beta and alpha2 frequency bands. The dynamics of studied EEG indices manifested in the parietal, temporal and occipital regions of the cerebral cortex to the greatest extent. The largest sex-related differences in the EEG parameters occur in puberty. Functional core of the wave components interaction that maintain the structure of the frequency-temporal EEG pattern is formed to 16-18 years in girls in alpha2-beta1 range, while in boys in alpha1-alpha2 range. Intensity of age-related rearrangements of the EEG pattern reflects the gradual maturation of electrogenesis in different brain structures and has individual features due to both genetic and environmental factors. Obtained quantitative indicators of formation with age of dynamic relationships between basic EEG rhythms permit to reveal children with disturbed or delayed development of the central nervous system.
Text of scientific work on the topic “Features of the time-frequency organization of the EEG pattern in children and adolescents in the North at different age periods”
UDC 612.821-053.4/.7(470.1/.2)
FEATURES OF TEMPORAL-FREQUENCY ORGANIZATION OF EEG PATTERN IN CHILDREN AND ADOLESCENTS IN THE NORTH AT DIFFERENT AGE PERIODS
© 2016 S. I. Soroko, V. P. Rozhkov, S. S. Bekshaev
Institute of Evolutionary Physiology and Biochemistry named after. I. M. Sechenov Russian Academy of Sciences,
Saint Petersburg
Using an original method for assessing the structure of interaction of EEG components (waves), the dynamics of the formation of patterns of bioelectrical activity of the brain and age-related changes in the relationships between the main frequency components of the EEG, characterizing the features of the development of the central nervous system in children and adolescents living in the difficult environmental conditions of the North of the Russian Federation, were studied. It has been established that the statistical structure of the interaction of EEG components undergoes significant changes with age and has its own topographic and gender differences. In the period from 7 to 18 years, the probability of interaction of waves of all frequency ranges of EEG rhythms with waves of the delta and theta ranges decreases, with a simultaneous increase in interaction with waves of the beta and alpha2 ranges. To the greatest extent, the dynamics of the analyzed EEG indicators are manifested in the parietal, temporal and occipital regions of the cerebral cortex. The greatest gender differences in the analyzed EEG parameters occur during the puberty period. By the age of 16-17, in girls, the functional core of the interaction of wave components, which supports the structure of the EEG pattern, is formed in the alpha2-beta1 range, while in boys - in the alpha2-alpha1 range. The severity of age-related changes in the EEG pattern reflects the gradual formation of electrogenesis of various brain structures and has individual characteristics determined by both genetic and environmental factors. The obtained quantitative indicators of the formation of dynamic relationships of the basic rhythms with age make it possible to identify children with impaired or delayed development of the central nervous system.
Key words: children, adolescents, age-related development, brain, EEG, North, adaptation
CARACTERISTICS OF TIME AND FREQUENCY EEG PATTERN IN CHILDREN AND ADOLESCENTS LIVING IN THE NORTH IN DIFFERENT AGE PERIODS
S. I. Soroko, V. P., Rozhkov, S. S. Bekshaev
I. M. Sechenov Institute of Evolutionary Physiology and Biochemistry of the Russian Academy of Sciences,
St. Petersburg, Russia
Features of CNS development have been investigated in children and adolescents living under the severe ecological conditions in the North of Russia. The original method for estimating a time structure of the EEG frequency components interrelations was used to study the dynamics of maturation of bioelectrical brain activity pattern and age-related changes of the interplay between the main EEG rhythms. It was found that the statistical structure of the interaction of the frequency components of EEG is undergoing a significant restructuring with age and has certain topography and gender differences. The period from 7 to 18 years of age is marked by a decrease in the probability of interaction of wave components of the main EEG frequency bands with components of delta and theta bands while simultaneously increasing interaction with the components of beta and alpha2 frequency bands. The dynamics of studied EEG indices manifested in the parietal, temporal and occipital regions of the cerebral cortex to the greatest extent. The largest sex-related differences in the EEG parameters occur in puberty. Functional core of the wave components interaction that maintain the structure of the frequency-temporal EEG pattern is formed to 16-18 years in girls in alpha2-beta1 range, while in boys - in alpha1-alpha2 range. Intensity of age-related rearrangements of the EEG pattern reflects the gradual maturation of electrogenesis in different brain structures and has individual features due to both genetic and environmental factors. Obtained quantitative indicators of formation with age of dynamic relationships between basic EEG rhythms permit to reveal children with disturbed or delayed development of the central nervous system.
Keywords: children, adolescents, brain development, EEG, the North, adaptation
Soroko S.I., Rozhkov V.P., Bekshaev S.S. Features of the time-frequency organization of the EEG pattern in children and adolescents in the North at different age periods // Human Ecology. 2016. No. 5. P. 36-43.
Soroko S. I., Rozhkov V. P., Bekshaev S. S. Caracteristics of Time and Frequency EEG Pattern in Children and Adolescents Living in the North in Different Age Periods. Ekologiya cheloveka. 2016, 5, pp. 36-43.
The socio-economic development of the Arctic zone is defined as one of the priority areas of state policy of the Russian Federation. In this regard, a comprehensive study of the medical and socio-economic problems of the population of the North, health protection and improving the quality of life is very relevant.
It is known that a complex of extreme environmental factors of the North (natural, man-made,
social) has pronounced stress-generating effects on the human body, with the greatest stress experienced by the child population. Increased loads on physiological systems and tension in the central mechanisms of regulation of functions in children living in unfavorable climatic conditions of the North determine the development of two types of negative reactions: reduction in reserve capacity and delay
pace of age development. These negative reactions are based on an increased level of costs for homeostatic regulation and maintenance of metabolism with the formation of a deficiency of bioenergetic substrate. In addition, through higher-order genes that control age-related development, unfavorable environmental factors can have epigenetic influences on the pace of age-related development by temporarily stopping or shifting one or another stage of development. Deviations from normal development that are not identified in childhood can subsequently lead to disruption of certain functions or to pronounced defects already in adulthood, significantly reducing a person’s quality of life.
In the literature there is a huge number of works devoted to the study of the age-related development of the central nervous system of children and adolescents, nosological forms of developmental disorders. In the conditions of the North, the influence of complex natural and social factors can determine the characteristics of age-related EEG maturation in children. However, there are still no sufficiently reliable methods for early detection of abnormalities in brain development at different stages of postnatal ontogenesis. In-depth fundamental research is required to search for local and spatial EEG markers that make it possible to monitor individual morpho-functional development of the brain at different age periods in specific living conditions.
The purpose of this study was to study the peculiarities of the dynamics of the formation of rhythmic patterns of bioelectrical activity and age-related changes in the relationships between the main frequency components of the EEG, characterizing the maturation of both individual cortical and subcortical structures and regulatory subcortical-cortical interactions in healthy children living in the European North of Russia.
Contingent of subjects. 44 boys and 42 girls from 7 to 17 years old - students of grades 1 - 11 of a rural secondary school in the Konoshsky district of the Arkhangelsk region took part in the study of the age-related formation of bioelectrical activity of the brain. The studies were carried out in compliance with the requirements of the Declaration of Helsinki, as approved by the Biomedical Research Ethics Committee of the Institute of Evolutionary Physiology and Biochemistry. I.M. Sechenov Russian Academy of Sciences protocol. The students' parents were informed about the purpose of the survey and gave consent to conduct it. Schoolchildren participated in the research voluntarily.
EEG study procedure. EEG was recorded on a computer electroencephalograph EEGA 21/26 “Encephalan-131-03” (NPKF “Medicom” MTD, Russia) in 21 leads according to international
system “10-20” in the band 0.5-70 Hz with a sampling frequency of 250 Hz. A monopolar lead was used with a combined reference electrode on the earlobes. EEG recordings were made in a sitting position. The results are presented for a state of quiet wakefulness with eyes closed.
EEG analysis. Digital filtering was previously used to limit the EEG frequency range to a band from 1.6 to 30 Hz. EEG fragments containing oculomotor and muscle artifacts were excluded. To analyze the EEG, original methods were used to study the dynamic structure of the time sequence of EEG waves. The EEG was converted into a sequence of periods (EEG waves), each of which, depending on the duration, belongs to one of the six EEG frequency ranges (P2: 17.5-30 Hz; P1: 12.5-17.5 Hz; a2: 9, 5-12.5 Hz; a1: 7-9.5 Hz; 0: 4-7 Hz and 5: 1.5-4 Hz). We estimated the conditional probability of the appearance of any frequency component of the EEG, provided that it was immediately preceded by another; this probability is equal to the probability of the transition from the previous frequency component to the subsequent one. Based on the numerical values of the probability of transitions between all specified frequency ranges, a matrix of transition probabilities of size 6 x 6 was compiled. For a visual representation of the transition probability matrices, oriented probability graphs were constructed. The vertices are the above frequency components of the EEG, the edges of the graph connect the EEG components of different frequency ranges, the thickness of the edge is proportional to the probability of the corresponding transition.
Statistical data analysis. To identify the relationship between changes in EEG parameters with age, Pearson correlation coefficients were calculated, and multiple linear regression analysis was used with ridge estimates of regression parameters with stepwise inclusion of predictors. When analyzing the topical features of age-related changes in EEG parameters, the predictors were estimates of the probability of transitions between all 6 frequency ranges (36 parameters for each EEG lead). Multiple correlation coefficients r, regression coefficients and coefficients of determination (r2) were analyzed.
To assess the age-related patterns of EEG pattern formation, all schoolchildren (86 people) were divided into three age groups: the youngest - from 7 to 10.9 years (n = 24), the middle - from 11 to 13.9 years (n = 25), the eldest - from 14 to 17.9 years (n = 37). Using two-factor analysis of variance (ANOVA), the influence of the factors “Gender” (2 gradations), “Age” (3 gradations), as well as the effect of their interaction on EEG parameters was assessed. Effects (F-test values) were analyzed with a significance level of p< 0,01. Для оценки возможности возрастной классификации детей по описанным выше матрицам вероятностей переходов в 21-м отведении использовали классический дискриминантный анализ
with step-by-step inclusion of predictors. Statistical processing of the obtained data was carried out using the $1a software package<лз1лса-Ш.
results
For 86 students, matrices of transition probabilities from one EEG frequency component to another were calculated, from which corresponding transition graphs were constructed in 21 EEG leads. Examples of such graphs for a 7- and 16-year-old schoolchild are shown in Fig. 1. The graphs show a structure of transitions that is repeated in many leads, characterizing a certain algorithm for replacing one EEG frequency component with another in their time sequence. Lines (edges) on each of the graphs emanating from most of the vertices (the vertices correspond to the main EEG frequency ranges) of the left column of the graph converge on the right column to 2-3 vertices (EEG ranges). This convergence of lines to individual ranges reflects the formation of a “functional core” of the interaction of EEG wave components, which plays a major role in maintaining this structure of the bioelectrical activity pattern. The core of such interaction in children from the lower grades (7-10 years old) is the theta and alpha1 frequency ranges, in adolescents from the older grades (14-17 years old) - alpha1 and alpha2 frequency ranges, that is, a “change” of functional nuclei of the low-frequency (theta) range to high-frequency (alpha1 and alpha2).
For elementary school students, a stable structure of transition probabilities is typical for
occipital, parietal and central leads. For most adolescents aged 14-17 years, probabilistic transitions are already well structured not only in the occipito-parietal and central, but also in the temporal (T5, T6, T3, T4) regions.
Correlation analysis makes it possible to quantify the dependence of changes in the probabilities of inter-frequency transitions on the student’s age. In Fig. 2 in the cells of the matrices (built similar to transition probability matrices, each matrix corresponds to a specific EEG lead), triangles display only significant correlation coefficients: the vertex of the triangle up characterizes an increase in the probability, the vertex down characterizes a decrease in the probability of a given transition. The presence of a regular structure in the matrices for all EEG leads attracts attention. Thus, in the columns designated 9 and 5, there are only icons with the top pointing downward, which reflects a decrease with age in the probability of a wave of any range (indicated vertically in the matrix) transitioning to waves of the delta and theta ranges of the EEG. In the columns designated a2, p1, p2, there are only icons with the top pointing upward, which reflects an increase with age in the probability of a wave of any range transitioning to waves in the beta1, beta2, and especially alpha2 range of EEG frequencies. It can be seen that the most pronounced age-related changes, in opposite directions, are associated with transitions to the alpha2 and theta ranges. A special place is occupied by the alpha 1 frequency range. The probability of transitions to this range in all EEG leads shows an age dependence
Fig.1. Topical features of the structure of mutual transitions of waves of different EEG frequency ranges in a student 7 (I) and 16 (II) years old p1, p2 - beta, a1, a2 - alpha, 9 - theta, 5 - delta components (waves) of the EEG. Transitions whose conditional probability exceeds 0.2 are shown. Fp1 ... 02 - EEG leads.
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Rice. 2. Changes in the probabilities of transitions between the wave components of the main EEG rhythms in various leads with age in schoolchildren (86 people)
5 ... p2 - EEG frequency ranges, Fp1 ... 02 - EEG leads. Triangle in a cell: with the apex down - a decrease, with the apex up - an increase with age in the probability of transitions between EEG components of different frequency ranges. Significance level: p< 0,05 - светлый треугольник, р < 0,01 - темный треугольник.
only in isolated cases. However, if you monitor the filling of the lines, then the alpha 1-range of EEG frequencies with age in schoolchildren reduces the connection with the slow-wave ranges and increases the connection with the alpha2-range, thereby acting as a factor regulating the stability of the EEG wave pattern
To comparatively assess the degree of connection between the age of children and changes in the wave pattern in each EEG lead, we used the multiple regression method, which made it possible to evaluate the effect of combined rearrangements of mutual transitions between components of all EEG frequency ranges, taking into account their mutual correlation (in order to reduce the redundancy of predictors, we used ridge regression). Determination coefficients characterizing the share of variability of the studied
EEG indicators, which can be explained by the influence of the age factor, vary in different leads from 0.20 to 0.49 (Table 1). Changes in the structure of transitions with age have certain topical features. Thus, the highest coefficients of determination between the analyzed parameters and age are revealed in the occipital (01, 02), parietal (P3, Rg, P4) and posterior temporal (T6, T5) leads, decreasing in the central and temporal (T4, T3) leads, and also in F8 and F3, reaching the lowest values in the frontal leads Fp1, Fpz, Fp2, F7, F4, Fz). Based on the absolute values of the coefficients of determination, it can be assumed that at school age the neuronal structures of the occipital, temporal and parietal regions develop most dynamically. At the same time, changes in the structure of transitions in the parietotemporal areas in
the right hemisphere (P4, T6, T4) are more closely related to age than the left (P3, T5, T3).
Table 1
Results of multiple regression between the variable “age of the student” and the probabilities of transitions
between all frequency components of the EEG (36 variables) separately for each lead
EEG lead r F df r2
Fp1 0.504 5.47* 5.80 0.208
Fpz 0.532 5.55* 5.70 0.232
Fp2 0.264 4.73* 6.79 0.208
F7 0.224 7.91* 3.82 0.196
F3 0.383 6.91** 7.78 0.327
Fz 0.596 5.90** 7.75 0.295
F4 0.524 4.23* 7.78 0.210
F8 0.635 5.72** 9.76 0.333
T3 0.632 5.01** 10.75 0.320
C3 0.703 7.32** 10.75 0.426
Cz 0.625 6.90** 7.75 0.335
C4 0.674 9.29** 7.78 0.405
T4 0.671 10.83** 6.79 0.409
T5 0.689 10.07** 7.78 0.427
P3 0.692 12.15** 6.79 0.440
Pz 0.682 13.40** 5.77 0.430
P4 0.712 11.46** 7.78 0.462
T6 0.723 9.26** 9.76 0.466
O1 0.732 12.88** 7.78 0.494
Oz 0.675 6.14** 9.66 0.381
O2 0.723 9.27** 9.76 0.466
Note. r - coefficient of multiple correlation
between the variable “student age” and independent variables, F - the corresponding value of the F-criterion, significance levels: * p< 0,0005, ** p < 0,0001; r2 - скорректированный на число степеней свободы (df) коэффициент детерминации.
The multiple correlation coefficient between the age of schoolchildren and the values of transition probabilities, calculated for the entire set of leads (at the same time, transitions whose correlation with age did not reach the significance level of 0.05 were excluded from the complete list of transitions in advance) was 0.89, adjusted r2 = 0, 72 (F (21.64) = 11.3, p< 0,0001). То есть 72 % от исходной изменчивости зависимой переменной (возраст) могут быть объяснены в рамках модели множественной линейной регрессии, где предикторами являются вероятности переходов в определенном наборе отведений ЭЭГ. В числе предикторов оказались: P3 (t/t) = -0,21; O2 (b2/t) = -0,18; C3 (b 1 /t) = -0,16; F7 (a1/t) = 0,25; T6 (d/t) = -0,20; P4 (b2/a1) = -0,21; O1 (t/ t) = -0,21; T5 (a1/a2) = -0,20; F8 (t/d) = -0,18; O1 (d/t) = -0,08; F8 (t/t) = 0,22; T6 (a1/t) = -0,26; C3 (d/t) = -0,19; C3 (b2/b1) = 0,16; F8 (b2/t) = 0,19; Fp1 (a1/a2) = -0,17; P4 (t/t) = -0,15; P3 (a2/d) = 0,11; C4 (a2/a2) = 0,16;
Fp2 (b2/b1) = 0.11; 02 (1/a2) = -0.11 (in brackets 1/ is the transition from component 1 to component ]). The sign of the regression coefficient characterizes the direction of the relationship between the variables: if the sign is positive, the probability of this transition increases with age, if the sign is negative, the probability of this transition decreases with age.
Using discriminant analysis based on the probabilities of EEG transitions, schoolchildren were divided into age groups. Of the entire set of transition probabilities, only 26 parameters were used for classification - according to the number of predictors obtained from the results of multiple linear regression analysis with ridge estimates of regression parameters. The separation results are presented in Fig. 3. It can be seen that the resulting sets for different age groups overlap slightly. By the degree of deviation from the center of the cluster of a particular schoolchild or his placement in another age group, one can judge whether the rate of formation of the EEG wave pattern is delayed or advanced.
° az A p O<к о о OfP® O ° d„ °o e A o o 6 -4 -2 0 2 46 Canonical re/foam 1 Rice. Fig. 3. Distribution of schoolchildren of different age groups (junior - junior, middle - middle, senior - senior) on the discriminant field. The transition probabilities of EEG components (waves), significant according to the results of multiple regression, were selected as predictors in the discriminant analysis. Peculiarities in the age-related dynamics of the formation of the EEG wave pattern in girls and boys are revealed (Table 2). According to analysis of variance, the main effect of the Gender factor is more pronounced in the parietotemporal regions than in the frontocentral regions and is accentuated in the leads of the right hemisphere. The influence of the Gender factor is that in boys the connection between alpha2- and the low-frequency alpha 1-band is more pronounced, and in girls the connection between alpha2- and the high-frequency beta frequency ranges is more pronounced. The effect of the interaction of factors associated with age dynamics is better manifested in EEG parameters of the frontal and temporal (also predominantly on the right) areas. It is mainly associated with a decrease in the likelihood of table 2 Differences in the probabilities of transitions between EEG frequency components and their age dynamics in girls and boys (ANOVA data for EEG leads) Transition between EEG frequency components EEG lead Main effect of the factor Gender Effect of interaction of factors Gender*Age Fp1 ß1-0 a1- 5 0-0 Fp2 ß2-0 a1-0 0-ß1 T4 ß2-a1 0-a1 ß2-0 a2-0 a1-0 a1-5 T6 a2-a1 a2- ß1 a1-ß1 a2-0 a1-0 P4 a2-a1 ß2-a1 a1-0 a1-5 O2 a2-a1 a2-ß1 a1-ß2 a1-a1 0-0 Note. p2 ... 5 - EEG components The probabilities of transitions are presented with the significance level of the influence of the factor Gender (interaction of the factors Gender and Age) p< 0,01. Отведения Fpz, F7, F8, F3, F4, Т3, С2, 02 в таблице не представлены из-за отсутствия значимых эффектов влияния фактора Пол и взаимодействия факторов. ity of transitions from the alpha and beta frequency ranges to the theta range. At the same time, a more rapid decrease in the probability of transition from the beta and alpha ranges to the theta frequency range in boys is observed between the junior and middle school age groups, while in girls - between the middle and older age groups. The discussion of the results Thus, based on the analysis, frequency components of the EEG were identified that determine age-related reorganization and the specificity of patterns of bioelectrical activity of the brain in northern schoolchildren. Quantitative indicators of the formation with age of the dynamic relationships of the main EEG rhythms in children and adolescents were obtained, taking into account gender characteristics, which make it possible to control the pace of age-related development and possible deviations in the dynamics of development. Thus, in primary schoolchildren, a stable structure of the temporal organization of EEG rhythms was found in the occipital, parietal and central leads. In most adolescents aged 14-17 years, the EEG pattern is well structured not only in the occipito-parietal and central, but also in the temporal regions. The data obtained confirm the idea of the sequential development of brain structures and the stage-by-stage formation of rhythmogenesis and integrative functions of the corresponding brain regions. It is known that the sensory and motor areas of the cortex mature by the primary school period, later multimodal and associative zones mature, and the formation of the frontal cortex continues until adulthood. At a younger age, the wave structure of the EEG pattern is less organized (diffuse) in nature. Gradually, with age, the structure of the EEG pattern begins to acquire an organized character and by the age of 17-18 it approaches that of adults. The core of the functional interaction of EEG wave components in children of primary school age is the theta and alpha1 frequency ranges, in older school age - alpha1 and alpha2 frequency ranges. In the period from 7 to 18 years, the probability of interaction of waves of all frequency ranges of EEG rhythms with waves of the delta and theta ranges decreases, with a simultaneous increase in interaction with waves of the beta and alpha2 ranges. To the greatest extent, the dynamics of the analyzed EEG indicators are manifested in the parietal and temporo-occipital regions of the cerebral cortex. The greatest gender differences in the analyzed EEG parameters occur during the puberty period. By the age of 16-17, in girls, the functional core of the interaction of wave components, which supports the structure of the EEG pattern, is formed in the alpha2-beta1 range, while in boys - in the alpha2-alpha1 range. However, it should be noted that the age-related formation of the EEG pattern in different areas of the cerebral cortex proceeds heterochronically, undergoing some disorganization with an increase in theta activity during puberty. These deviations from the general dynamics are most pronounced during puberty in girls. Studies have shown that children in the Arkhangelsk region, in comparison with children living in the Moscow region, have a delay in puberty of one to two years. This may be due to the influence of climatic and geographical conditions of the environment, which determine the characteristics of the hormonal development of children in the northern regions. One of the factors of ecological unfavorability of the human habitat in the North is the lack or excess of chemical elements in soil and water. Residents of the Arkhangelsk region have a deficiency of calcium, magnesium, phosphorus, iodine, fluorine, iron, selenium, cobalt, copper and other elements. Disturbances in micro- and macroelement balance were also identified in children and adolescents, whose EEG data are presented in this work. This can also affect the nature of age-related morphofunctional development of various body systems, including the central nervous system, since essential and other chemical elements are an integral part of many proteins and are involved in the most important molecular biochemical processes, and some of them are toxic. The nature of adaptive changes and the degree their severity is largely determined by the adaptive capabilities of the body, depending on individual typological characteristics, sensitivity and resistance to certain influences. The study of the developmental features of the child’s body and the formation of the EEG structure is an important basis for the formation of ideas about the different stages of ontogenesis, early detection of disorders and the development of possible methods for their correction. The work was carried out under the Basic Research Program No. 18 of the Presidium of the Russian Academy of Sciences. Bibliography 1. Boyko E. R. Physiological and biochemical foundations of human life in the North. Ekaterinburg: Ural Branch of the Russian Academy of Sciences, 2005. 190 p. 2. Gorbachev A.L., Dobrodeeva L.K., Tedder Yu.R., Shatsova E.N. Biogeochemical characteristics of the Northern regions. 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Development of cortical and subcortical brain structures in childhood and adolescence: a structural MRI study // Developmental Medicine and Child Neurology. 2002. Vol. 44, N 1. P. 4-16. 1. Bojko E. R. Fiziologo-biochimicheskie osnovy zhiznedeyatelnosti cheloveka na Severe. Yekaterinburg, 2005. 190 p. 2. Gorbachev A. L., Dobrodeeva L. K., Tedder Yu. R., Shacova E. N. Biogeochemical characteristics of the northern regions. Trace element status of the population of the Arkhangelsk region and the forecast of endemic diseases. Ekologiya cheloveka. 2007, 1, pp. 4-11. 3. Gudkov A. B., Lukmanova I. B., Ramenskaya E. B. Chelovek v Pripolyarnom regione Evropejskogo Severa. Ekologo-fiziologicheskie aspekty. Arkhangelsk, 2013, 184 p. 4. Demin D. B., Poskotinova L. V., Krivonogova E. V. Variants of EEG Formation in Adolescents Living in Subpolar and Polar Regions of the Northern Russia. Vestnik Severnogo (Arkticheskogo) federalnogo universiteta, seriya "Mediko-biologicheskie nauki" . 2013, 1, pp. 41-45. 5. Dzhos Yu. S., Nekhoroshkova A. N., Gribanov A. V. Peculiarities of EEG and DC-potential of the Brain in Northern Schoolchildren. Ekologiya cheloveka. 2014, 12, pp. 15-20. 6. Kubasov R. V., Demin D. B., Tipisova E. V., Tkachev A. V. Hormonal provision of pituitary-thyroid-gonad gland system in boys during puberty living in Konosha District of the Arkhangelsk Region. Ekologiya cheloveka. 2004, 1 (4), pp. 265-268. 7. Kudrin A. V., Gromova O. A. Mikroelementyi v nevro-logii. Moscow, 2006, 304 p. 8. Lukmanova N. B., Volokitina T. V., Gudkov A. B., Safonova O. A. Changes of Psychomotor development parameters in 7-9 years. o. children. Ekologiya cheloveka. 2014, 8, pp. 13-19. 9. Nifontova O. L., Gudkov A. B., Shherbakova A. Je. Description of parameters of cardiac rhythm in indigenous children in Khanty-Mansiisky autonomous area. Ekologiya cheloveka. 2007, 1 1, pp. 41-44. 10. Novikova L. A., Farber D. A. Funkcionalnoe sozrevanie kory i podkorkovych struktur v razlichnye periody po dannym elektroencefalograficheskich issledovanij. Rukovodstvo po fiziologii. Ed. V. N. Chernigovsky. Leningrad, 1975, pp. 491-522. 11. Postanovlenie Pravitelstva RF from 04/21/2014 g. No. 366 “Ob utverzhdenii Gosudarstvennoj programmy Rossijskoj Federacii “Social-ekonomicheskoe razvitie Arkticheskoj zony Rossijskoj Federacii na period do 2020 goda” Dostup iz sprav.- pravovoj sistemy “KonsultantPlyus”. 12. Soroko S. I., Burykh E. A., Bekshaev S. S., Sidorenko G. V., Sergeeva E. G., Khovanskich A. E., Kormilicyn B. N., Moralev S. N., Yagodina O. V., Dobrodeeva L. K., Maksimova I. A., Protasova O. V. Characteristics of the brain system activity and vegetative function formation in children under conditions of the European north (a problem study). Rossiiskii fiziologicheskii jurnal imeni I. M. Sechenova / Rossiiskaia akademiia nauk. 2006, 92 (8), pp. 905-929. 13. Soroko S. I., Maksimova I. A., Protasova O. V Age and gender characteristics of the content of macro- and trace elements in the organisms of the children from the European North. Phiziologiya cheloveka. 2014, 40 (6), pp. 23-33. 14. Tkachev A. V. Vliyanie prirodnych faktorov Severa na endokrinnuyu sistemu cheloveka. Problemy ekologii cheloveka. Arkhangelsk. 2000, pp. 209-224. 15. Ciceroshin M. N., Shepovalnikov A. N. Stanovlenie integrativnojfunkcii mozga. St. Petersburg, 2009, 250 p. 16. Baars B. J. The conscious access hypothesis: Origins and recent evidence. Trends in Cognitive Sciences. 2002, 6 (1), pp. 47-52. 17. Clarke A. R., Barry R. J., Dupuy F. E., McCarthy R., Selikowitz M., Heaven P. C. L. Childhood EEG as a predictor of adult attention-deficit/hyperactivity disorder. Clinical Neurophysiology. 2011, 122, pp. 73-80. 18. Loo S. K., Makeig S. Clinical utility of EEG in attention-deficit/hyperactivity disorder: a research update. Neurotherapeutics. 2012, 9 (3), pp. 569-587. 19. Sowell E. R., Trauner D. A., Gamst A., Jernigan T. L. Development of cortical and subcortical brain structures in childhood and adolescence: a structural MRI study. Developmental Medicine and Child Neurology. 2002, 44 (1), pp. 4-16. Contact Information: Rozhkov Vladimir Pavlovich - Candidate of Biological Sciences, leading researcher at the Institute of Evolutionary Physiology and Biochemistry named after. I. M. Sechenov Russian Academy of Sciences" Address: 194223, St. Petersburg, Thorez Ave., 44 In developmental psychophysiology, almost all the methods that are used when working with a contingent of adult subjects are used (see Chapter 2). However, there are age specificities in the use of traditional methods, which are determined by a number of circumstances. First, the indicators obtained using these methods have large age differences. For example, the electroencephalogram and, accordingly, the indicators obtained with its help change significantly during ontogenesis. Secondly, these changes (in their qualitative and quantitative expression) can act in parallel both as a subject of research, and as a way to assess the dynamics of brain maturation, and as a tool/means for studying the emergence and functioning of physiological conditions of mental development. Moreover, it is the latter that is of greatest interest for developmental psychophysiology. All three aspects of the study of EEG in ontogenesis are certainly consistent with each other and complement each other, but in terms of content they differ very significantly, and therefore they can be considered separately from each other. For this reason, both in specific scientific research and in practice, the emphasis is often placed on only one or two aspects. However, despite the fact that for developmental psychophysiology the third aspect is of greatest importance, i.e. How EEG indicators can be used to assess the physiological prerequisites and/or conditions of mental development, the depth of study and understanding of this problem depends decisively on the degree of elaboration of the first two aspects of EEG study. The main feature of the EEG, which makes it an indispensable tool for developmental psychophysiology, is its spontaneous, autonomous nature. Regular electrical activity of the brain can be detected already in the fetus, and stops only with the onset of death. At the same time, age-related changes in the bioelectrical activity of the brain cover the entire period of ontogenesis from the moment of its occurrence at a certain (and not yet precisely established) stage of intrauterine brain development until the death of a person. Another important circumstance that allows the productive use of EEG in the study of brain ontogenesis is the possibility of quantitative assessment of the changes occurring. Studies of ontogenetic transformations of the EEG are very numerous. The age-related dynamics of the EEG are studied at rest, in other functional states (sleep, active wakefulness, etc.), as well as under the influence of various stimuli (visual, auditory, tactile). Based on many observations, indicators have been identified by which age-related transformations are judged throughout ontogenesis, both in the process of maturation (see Chapter 12.1.1.) and during aging. First of all, these are the features of the frequency-amplitude spectrum of the local EEG, i.e. activity recorded at individual points of the cerebral cortex. In order to study the relationship of bioelectrical activity recorded from different points of the cortex, spectral-correlation analysis is used (see Chapter 2.1.1) with an assessment of the coherence functions of individual rhythmic components. Age-related changes in the rhythmic composition of the EEG. The most studied in this regard are age-related changes in the frequency-amplitude spectrum of the EEG in different areas of the cerebral cortex. Visual analysis of the EEG shows that in awake newborns the EEG is dominated by slow irregular oscillations with a frequency of 1–3 Hz and an amplitude of 20 μV. However, their EEG frequency spectrum contains frequencies in the range from 0.5 to 15 Hz. The first manifestations of rhythmic orderliness appear in the central zones, starting from the third month of life. During the first year of life, an increase in the frequency and stabilization of the basic rhythm of the child’s electroencephalogram is observed. The tendency towards an increase in the dominant frequency continues at further stages of development. By 3 years this is already a rhythm with a frequency of 7–8 Hz, by 6 years – 9–10 Hz (Farber, Alferova, 1972). One of the most controversial is the question of how to qualify the rhythmic components of the EEG of young children, i.e. how to correlate the classification of rhythms by frequency ranges accepted for adults (see Chapter 2.1.1) with those rhythmic components that are present in the EEG of children in the first years of life. There are two alternative approaches to solving this issue. The first assumes that the delta, theta, alpha and beta frequency ranges have different origins and functional significance. In infancy, slow activity turns out to be more powerful, and in further ontogenesis there is a change in the dominance of activity from slow to fast frequency rhythmic components. In other words, each EEG frequency band dominates in ontogeny one after another (Garshe, 1954). According to this logic, 4 periods were identified in the formation of bioelectrical activity of the brain: 1 period (up to 18 months) – dominance of delta activity, mainly in the central-parietal leads; 2nd period (1.5 years – 5 years) – dominance of theta activity; 3rd period (6 – 10 years) – dominance of alpha activity (labile phase); 4th period (after 10 years of life) dominance of alpha activity (stable phase). In the last two periods, maximum activity occurs in the occipital regions. Based on this, it was proposed to consider the ratio of alpha to theta activity as an indicator (index) of brain maturity (Matousek, Petersen, 1973). Another approach considers the basic one, i.e. the dominant rhythm in the electroencephalogram, regardless of its frequency parameters, as an ontogenetic analogue of the alpha rhythm. The basis for such an interpretation is contained in the functional features of the dominant rhythm in the EEG. They are expressed in the “principle of functional topography” (Kuhlman, 1980). In accordance with this principle, identification of the frequency component (rhythm) is carried out on the basis of three criteria: 1) frequency of the rhythmic component; 2) the spatial location of its maximum in certain areas of the cerebral cortex; 3) EEG reactivity to functional loads. Applying this principle to the analysis of the EEG of infants, T.A. Stroganova showed that the frequency component of 6–7 Hz, recorded in the occipital region, can be considered as a functional analogue of the alpha rhythm or as the alpha rhythm itself. Since this frequency component has a small spectral density in the state of visual attention, but becomes dominant in a uniform dark field of vision, which, as is known, characterizes the alpha rhythm of an adult (Stroganova et al., 1999). The stated position seems convincingly argued. Nevertheless, the problem as a whole remains unsolved, because the functional significance of the remaining rhythmic components of the EEG of infants and their relationship with the EEG rhythms of an adult: delta, theta and beta are not clear. From the above, it becomes clear why the problem of the relationship between theta and alpha rhythms in ontogenesis is a subject of debate. The theta rhythm is still often considered as a functional precursor of the alpha rhythm, and thus it is recognized that the alpha rhythm is virtually absent in the EEG of young children. Researchers who adhere to this position do not consider it possible to consider the rhythmic activity dominant in the EEG of young children as the alpha rhythm (Shepovalnikov et al., 1979). However, regardless of how these frequency components of the EEG are interpreted, age-related dynamics, indicating a gradual shift in the frequency of the dominant rhythm towards higher values in the range from the theta rhythm to the high-frequency alpha rhythm, is an indisputable fact (for example, Fig. 13.1). Heterogeneity of the alpha rhythm. It has been established that the alpha range is heterogeneous, and depending on the frequency, a number of subcomponents can be distinguished that apparently have different functional significance. A significant argument in favor of identifying narrow-band alpha subbands is the ontogenetic dynamics of their maturation. The three sub-bands include: alpha 1 – 7.7 – 8.9 Hz; alpha 2 – 9.3 – 10.5 Hz; alpha 3 – 10.9 – 12.5 Hz (Alferova, Farber, 1990). From 4 to 8 years, alpha 1 dominates, after 10 years, alpha 2 dominates, and at 16 to 17 years, alpha 3 predominates in the spectrum. The components of the alpha rhythm also have different topography: the alpha-1 rhythm is more pronounced in the posterior parts of the cortex, mainly in the parietal ones. It is considered local in contrast to alpha 2, which is widely distributed in the cortex, peaking in the occipital region. The third alpha component, the so-called murhythm, has a focus of activity in the anterior regions: the sensorimotor areas of the cortex. It also has a local character, since its power decreases sharply with distance from the central zones. The general trend of changes in the main rhythmic components is manifested in a decrease in the severity of the slow component alpha-1 with age. This component of the alpha rhythm behaves like the theta and delta ranges, the power of which decreases with age, and the power of the alpha 2 and alpha 3 components, like the beta range, increases. However, beta activity in normal healthy children is low in amplitude and power, and in some studies this frequency range is not even manipulated due to its relatively rare occurrence in normal samples. Features of EEG in puberty. The progressive dynamics of EEG frequency characteristics disappear in adolescence. At the initial stages of puberty, when the activity of the hypothalamic-pituitary region in the deep structures of the brain increases, the bioelectrical activity of the cerebral cortex changes significantly. In the EEG, the power of slow-wave components, including alpha-1, increases, and the power of alpha-2 and alpha-3 decreases. During puberty, differences in biological age become noticeable, especially between the sexes. For example, in girls 12–13 years old (experiencing stages II and III of puberty), the EEG is characterized by greater intensity of the theta rhythm and alpha 1 component compared to boys. At 14–15 years old, the opposite picture is observed. The girls are completing their finals ( TU and U) the stage of puberty, when the activity of the hypothalamic-pituitary region decreases and negative trends in the EEG gradually disappear. In boys at this age, stages II and III of puberty predominate and the signs of regression listed above are observed. By the age of 16, these differences between the sexes practically disappear, since most adolescents enter the final stage of puberty. The progressive direction of development is being restored. The frequency of the basic EEG rhythm increases again and acquires values close to the adult type. Features of EEG in aging. During the aging process, significant changes occur in the pattern of electrical activity in the brain. It has been established that after 60 years there is a slowdown in the frequency of the main EEG rhythms, primarily in the alpha rhythm range. In persons aged 17–19 years and 40–59 years, the frequency of the alpha rhythm is the same and is approximately 10 Hz. By age 90, it drops to 8.6 Hz. Slowing of the alpha rhythm frequency is called the most stable “EEG symptom” of brain aging (Frolkis, 1991). Along with this, slow activity (delta and theta rhythms) increases, and the number of theta waves is greater in individuals at risk of developing vascular psychology. Along with this, in people over 100 years old - long-livers with a satisfactory state of health and preserved mental functions - the dominant rhythm in the occipital region is within the range of 8 - 12 Hz. Regional dynamics of maturation. Until now, when discussing the age-related dynamics of the EEG, we have not specifically analyzed the problem of regional differences, i.e. differences existing between EEG indicators of different cortical zones in both hemispheres. However, such differences exist, and it is possible to identify a certain sequence of maturation of individual cortical zones based on EEG indicators. This is evidenced, for example, by the data of American physiologists Hudspeth and Pribram, who traced the maturation trajectories (from 1 to 21 years) of the EEG frequency spectrum of different areas of the human brain. Based on EEG indicators, they identified several stages of maturation. For example, the first covers a period from 1 to 6 years and is characterized by a rapid and synchronous rate of maturation of all zones of the cortex. The second stage lasts from 6 to 10.5 years, and the peak of maturation is reached in the posterior sections of the cortex at 7.5 years, after which the anterior sections of the cortex begin to develop rapidly, which are associated with the implementation of voluntary regulation and control of behavior. After 10.5 years, the synchrony of maturation is disrupted, and 4 independent maturation trajectories are distinguished. According to EEG indicators, the central areas of the cerebral cortex are ontogenetically the earliest maturing zone, and the left frontal, on the contrary, matures the latest; its maturation is associated with the formation of the leading role of the anterior parts of the left hemisphere in organizing information processing processes (Hudspeth, Pribram, 1992). Relatively late periods of maturation of the left frontal zone of the cortex were also noted repeatedly in the works of D. A. Farber and colleagues. Quantitative assessment of maturation dynamics by indicators EEG. Repeated attempts have been made to quantitatively analyze EEG parameters in order to identify mathematically expressed patterns of their ontogenetic dynamics. Typically, various types of regression analyzes (linear, nonlinear, and multiple regressions) have been used to estimate the age-related dynamics of power density spectra of individual spectral bands (delta to beta) (e.g., Gasser et al., 1988). The results obtained generally indicate that changes in the relative and absolute power of the spectra and the severity of individual EEG rhythms in ontogenesis are nonlinear. The most adequate description of experimental data is obtained when using polynomials of the second to fifth degree in regression analysis. The use of multidimensional scaling appears promising. For example, one recent study attempted to improve a method for quantifying age-related changes in EEG in the range from 0.7 to 78 years. Multidimensional scaling of spectral data from 40 cortical points made it possible to detect the presence of a special “age factor”, which turned out to be nonlinearly related to chronological age. As a result of the analysis of age-related changes in the spectral composition of the EEG, a Maturation Scale of Electrical Brain Activity was proposed, determined on the basis of the logarithm of the ratio of age predicted from EEG data and chronological age (Wackerman, Matousek, 1998). In general, assessing the level of maturity of the cortex and other brain structures using the EEG method has a very important clinical and diagnostic aspect, and visual analysis of individual EEG recordings still plays a special role in this, which cannot be filled by statistical methods. For the purpose of standardized and unified assessment of EEG in children, a special method of EEG analysis was developed, based on the structuring of expert knowledge in the field of visual analysis (Machinskaya et al., 1995). Figure 13.2 shows a general diagram showing the main components. Created on the basis of the structural organization of knowledge of specialist experts, this scheme for describing the EEG can can be used for individual diagnosis of the state of the central nervous system of children, as well as for research purposes in determining the characteristic features of the EEG of various groups of subjects. Age-related features of the spatial organization of the EEG. These features have been studied less than the age-related dynamics of individual EEG rhythms. Meanwhile, the importance of research into the spatial organization of biocurrents is very great for the following reasons. Back in the 70s, the outstanding Russian physiologist M.N. Livanov formulated the position of a high level of synchronicity (and coherence) of oscillations of brain biopotentials as a condition conducive to the emergence of a functional connection between brain structures that are directly involved in systemic interaction. The study of the features of spatial synchronization of biopotentials of the cerebral cortex during different types of activity in adults showed that the degree of distant synchronization of biopotentials of different zones of the cortex under activity conditions increases, but rather selectively. The synchronicity of the biopotentials of those cortical zones that form functional associations involved in ensuring specific activities increases. Consequently, the study of indicators of distant synchronization, reflecting age-related features of interzonal interaction in ontogenesis, can provide new grounds for understanding the systemic mechanisms of brain functioning, which undoubtedly play a large role in mental development at each stage of ontogenesis. Quantifying spatial synchronization, i.e. the degree of coincidence of the dynamics of brain biocurrents recorded in different zones of the cortex (taken in pairs) allows one to judge how the interaction between these zones occurs. The study of spatial synchronization (and coherence) of brain biopotentials in newborns and infants showed that the level of interzonal interaction at this age is very low. It is assumed that the mechanism that ensures the spatial organization of the field of biopotentials in young children is not yet developed and is gradually formed as the brain matures (Shepovalnikov et al., 1979). It follows from this that the possibilities of systemic unification of the cerebral cortex at an early age are relatively small and gradually increase as they grow older. Currently, the degree of interzonal synchrony of biopotentials is assessed by calculating the coherence functions of biopotentials of the corresponding zones of the cortex, and the assessment is carried out, as a rule, for each frequency range separately. For example, in 5-year-old children, coherence is calculated in the theta band, since the theta rhythm is the dominant EEG rhythm at this age. At school age and older, coherence is calculated in the alpha rhythm band as a whole or separately for each of its components. As interzonal interaction forms, the general rule of distance begins to clearly appear: the level of coherence is relatively high between close points of the cortex and decreases with increasing distance between zones. However, against this general background there are some peculiarities. The average level of coherence increases with age, but unevenly. The nonlinear nature of these changes is illustrated by the following data: in the anterior parts of the cortex the level of coherence increases from 6 to 9–10 years, then there is a decline by 12–14 years (during puberty) and an increase again by 16–17 years (Alferova, Farber , 1990). These, however, do not exhaust all the features of the formation of interzonal interaction in ontogenesis. The study of distant synchronization and coherence functions in ontogenesis has many problems, one of them is that the synchronization of brain potentials (and the level of coherence) depends not only on age, but also on a number of other factors: 1) the functional state of the subject; 2) the nature of the activity performed; 3) individual characteristics of interhemispheric asymmetry (profile of lateral organization) of a child and an adult. Research in this direction is scarce, and so far there is no clear picture describing the age-related dynamics in the formation of distant synchronization and intercentral interaction of the cerebral cortex zones in the process of one or another activity. However, the available data are sufficient to assert that the systemic mechanisms of intercentral interaction, necessary to ensure any mental activity, go through a long process of formation in ontogenesis. Its general line is the transition from relatively poorly coordinated regional manifestations of activity, which, due to the immaturity of the brain’s conductive systems, are characteristic of children as early as 7–8 years old, to an increasing degree of synchronization and specific (depending on the nature of the task) consistency in the intercentral interaction of zones cerebral cortex in adolescence. When studying neurophysiological processes The following methods are used: Conditioned reflex method Method for recording the activity of brain formations (EEG), evoked potential: optical and electrophysiological methods for recording multicellular activity of groups of neurons. Study of brain processes that provide behavior of mental processes using electronic computing technology. Neurochemical methods to determine changes in the rate of formation and quantity of neurohormones, entering the blood. 1. Method of implanting electrodes, 2. Split brain method, 3. Method of observing people with organic lesions of the central nervous system, 4. Testing, 5. Observation. Currently, the study method is used activities of functional systems, which ensures systematic approach to the study of GNI. Thus the content VND - study of conditioned reflex activity in the interaction of + and - conditioned reflexes with each other Since when determining the conditions for this interactions are transitioning from normal to a pathological state of nervous system functions: the balance between nervous processes is disturbed and then the ability to adequately respond to influences is impaired contributing environment or internal processes that provoke mental attitude and behavior. Age-related features of EEG. Electrical activity of the fetal brain appears at the age of 2 months, it is low-amplitude, has an intermittent, irregular character. Interhemispheric EEG asymmetry is observed. The EEG of a newborn is also arrhythmic fluctuations, a reaction is observed activation to fairly strong irritations - sound, light. The EEG of infants and toddlers is characterized by the presence of phi rhythms, gamma rhythms. The amplitude of the waves reaches 80 µV. The EEG of preschool children is dominated by two types of waves: alpha and phi rhythm, the latter is recorded in the form of groups of high-amplitude oscillations. EEG of schoolchildren from 7 to 12 years old. Stabilization and increase basic EEG rhythm, alpha rhythm stability. By the age of 16-18, the EEG of children is identical to the EEG of adults No. 31. Medulla oblongata and pons: structure, functions, age characteristics. The medulla oblongata is a direct continuation of the spinal cord. Its lower border is considered to be the place of exit of the roots of the 1st cervical spinal nerve or the decussation of the pyramids, the upper border is the posterior edge of the bridge. The length of the medulla oblongata is about 25 mm, its shape approaches a truncated cone, with the base facing upward. The medulla oblongata is built of white and gray matter. The gray matter of the medulla oblongata is represented by the nuclei of IX, X, XI, XII pairs of cranial nerves, olives, reticular formation, centers of respiration and circulation. The white matter is formed by nerve fibers that make up the corresponding pathways. The motor pathways (descending) are located in the anterior parts of the medulla oblongata, the sensory (ascending) pathways lie more dorsally. The reticular formation is a collection of cells, cell clusters and nerve fibers that form a network located in the brain stem (medulla oblongata, pons and midbrain). The reticular formation is connected to all sense organs, motor and sensory areas of the cerebral cortex, the thalamus and hypothalamus, and the spinal cord. It regulates the level of excitability and tone of various parts of the nervous system, including the cerebral cortex, and is involved in the regulation of the level of consciousness, emotions, sleep and wakefulness, autonomic functions, and purposeful movements. Above the medulla oblongata is the pons, and behind it is the cerebellum. Bridge (Varoliev pons) has the appearance of a transversely thickened ridge, from the lateral side of which the middle cerebellar peduncles extend to the right and left. The posterior surface of the pons, covered by the cerebellum, participates in the formation of the rhomboid fossa. In the posterior part of the bridge (tegmentum) there is a reticular formation, where the nuclei of the V, VI, VII, VIII pairs of cranial nerves lie, and the ascending pathways of the bridge pass. The anterior part of the bridge consists of nerve fibers that form pathways, among which are the nuclei of gray matter. The pathways of the anterior part of the pons connect the cerebral cortex with the spinal cord, with the motor nuclei of the cranial nerves and the cerebellar cortex. The medulla oblongata and the pons perform the most important functions. The sensitive nuclei of the cranial nerves, located in these parts of the brain, receive nerve impulses from the scalp, mucous membranes of the mouth and nasal cavity, pharynx and larynx, from the digestive and respiratory organs, from the organ of vision and organ of hearing, from the vestibular apparatus, heart and blood vessels . Along the axons of the cells of the motor and vegetative (parasympathetic) nuclei of the medulla oblongata and the pons, impulses follow not only to the skeletal muscles of the head (masticatory, facial, tongue and pharynx), but also to the smooth muscles of the digestive, respiratory and cardiovascular systems, to the salivary and other numerous glands. Through the nuclei of the medulla oblongata, many reflex acts are performed, including protective ones (coughing, blinking, tearing, sneezing). The nerve centers (nuclei) of the medulla oblongata are involved in reflex acts of swallowing and the secretory function of the digestive glands. The vestibular (vestibular) nuclei, in which the vestibular-spinal tract originates, perform complex reflex acts of redistribution of skeletal muscle tone, balance, and provide a “standing posture.” These reflexes are called setting reflexes. The most important respiratory and vasomotor (cardiovascular) centers located in the medulla oblongata are involved in the regulation of respiratory function (pulmonary ventilation), the activity of the heart and blood vessels. Damage to these centers leads to death. With damage to the medulla oblongata, breathing disorders, cardiac activity, vascular tone, swallowing disorders can be observed - bulbar disorders, which can lead to death. The medulla oblongata is fully developed and functionally mature at the time of birth. Its mass together with the bridge in a newborn is 8 g, which is 2℅ of the mass of the brain. The nerve cells of a newborn have long processes and their cytoplasm contains tigroid substance. Cell pigmentation intensifies from 3 to 4 years of age and increases until puberty. By one and a half years of a child’s life, the number of cells in the center of the vagus nerve increases and the cells of the medulla oblongata are well differentiated. The length of neuron processes increases significantly. By the age of 7 years, the nuclei of the vagus nerve are formed in the same way as in an adult. Thank you The site provides reference information for informational purposes only. Diagnosis and treatment of diseases must be carried out under the supervision of a specialist. All drugs have contraindications. Consultation with a specialist is required! The activity of the brain, the state of its anatomical structures, the presence of pathologies are studied and recorded using various methods - electroencephalography, rheoencephalography, computed tomography, etc. A huge role in identifying various abnormalities in the functioning of brain structures belongs to methods of studying its electrical activity, in particular electroencephalography. The functional activity of the human brain depends on the activity of the median structures - reticular formation
And forebrain, which determine the rhythm, general structure and dynamics of the electroencephalogram. A large number of connections of the reticular formation and forebrain with other structures and the cortex determine the symmetry of the EEG, and its relative “sameness” for the entire brain. An EEG is taken to determine the activity of the brain in case of various lesions of the central nervous system, for example, with neuroinfections (poliomyelitis, etc.), meningitis, encephalitis, etc. Based on the EEG results, it is possible to assess the degree of brain damage due to various causes, and clarify specific location that has been damaged. The EEG is taken according to a standard protocol, which takes into account recordings in a state of wakefulness or sleep (infants), with special tests. Routine tests for EEG are: These tests are performed on all adults and children when taking an EEG, regardless of age and pathology. In addition, additional tests may be used when taking an EEG, for example: Today, the electroencephalogram is widely used in the practice of neurologists, since this method makes it possible to diagnose epilepsy, vascular, inflammatory and degenerative lesions of the brain. In addition, EEG helps to determine the specific location of tumors, cysts and traumatic damage to brain structures. An electroencephalogram with irritation of the patient by light or sound makes it possible to distinguish true visual and hearing impairments from hysterical ones, or their simulation. EEG is used in intensive care units for dynamic monitoring of the condition of patients in a coma. The disappearance of signs of electrical activity of the brain on the EEG is a sign of human death. Electroencephalograms for children under 14 years of age are taken only in specialized children's hospitals where pediatricians work. That is, you need to go to the children's hospital, find the neurology department and ask when the EEG is taken. Psychiatric clinics, as a rule, do not take EEGs for young children. In addition, private medical centers specializing in diagnostics and treatment of neurological pathology, also provide EEG services for both children and adults. You can contact a multidisciplinary private clinic, where there are neurologists who will take an EEG and decipher the recording. An electroencephalogram should be taken only after a full night's rest, in the absence of stressful situations and psychomotor agitation. Two days before the EEG is taken, it is necessary to exclude alcoholic beverages, sleeping pills, sedatives and anticonvulsants, tranquilizers and caffeine. To record an EEG, a cap is placed on the baby's head, under which the doctor places electrodes. The skin under the electrodes is wetted with water or gel. Two inactive electrodes are placed on the ears. Then, using alligator clips, the electrodes are connected to the wires connected to the device - the encephalograph. Since electrical currents are very small, an amplifier is always needed, otherwise brain activity will simply not be recorded. It is the small current strength that is the key to the absolute safety and harmlessness of EEG, even for infants. To begin the examination, the child's head should be placed flat. Anterior tilt should not be allowed as this may cause artifacts that will be misinterpreted. EEGs are taken for infants during sleep, which occurs after feeding. Wash your child's hair before taking the EEG. Do not feed the baby before leaving the house; this is done immediately before the test so that the baby eats and falls asleep - after all, it is at this time that the EEG is taken. To do this, prepare formula or express breast milk into a bottle that you use in the hospital. Up to 3 years of age, EEG is taken only in a state of sleep. Children over 3 years old can stay awake, but to keep your baby calm, take a toy, book, or anything else that will distract the child. The child should be calm during the EEG. Typically, the EEG is recorded as a background curve, and tests with opening and closing the eyes, hyperventilation (slow and deep breathing), and photostimulation are also performed. These tests are part of the EEG protocol, and are performed on absolutely everyone - both adults and children. Sometimes they ask you to clench your fingers into a fist, listen to various sounds, etc. Opening the eyes allows us to assess the activity of inhibition processes, and closing them allows us to assess the activity of excitation. Hyperventilation can be carried out in children after 3 years of age in the form of a game - for example, asking the child to inflate a balloon. Such rare and deep inhalations and exhalations last for 2–3 minutes. This test allows you to diagnose latent epilepsy, inflammation of the structures and membranes of the brain, tumors, dysfunction, fatigue and stress. Photostimulation is carried out with the eyes closed and the light blinking. The test allows you to assess the degree of delay in the child’s mental, physical, speech and mental development, as well as the presence of foci of epileptic activity. The human EEG contains alpha, beta, delta and theta rhythms, which have different characteristics and reflect certain types of brain activity. Alpha rhythm has a frequency of 8 – 14 Hz, reflects a state of rest and is recorded in a person who is awake, but with his eyes closed. This rhythm is normally regular, the maximum intensity is recorded in the area of the back of the head and the crown. The alpha rhythm ceases to be detected when any motor stimuli appear. Beta rhythm has a frequency of 13 – 30 Hz, but reflects the state of anxiety, restlessness, depression and the use of sedative medications. The beta rhythm is recorded with maximum intensity over the frontal lobes of the brain. Theta rhythm has a frequency of 4–7 Hz and an amplitude of 25–35 μV, reflecting the state of natural sleep. This rhythm is a normal component of the adult EEG. And in children this type of rhythm on the EEG predominates. Delta rhythm has a frequency of 0.5 - 3 Hz, it reflects the state of natural sleep. It can also be recorded in a limited amount during wakefulness, a maximum of 15% of all EEG rhythms. The amplitude of the delta rhythm is normally low - up to 40 μV. If there is an excess of amplitude above 40 μV, and this rhythm is recorded for more than 15% of the time, then it is classified as pathological. Such a pathological delta rhythm indicates a dysfunction of the brain, and it appears precisely over the area where pathological changes develop. The appearance of a delta rhythm in all parts of the brain indicates the development of damage to the structures of the central nervous system, which is caused by liver dysfunction, and is proportional to the severity of the disturbance of consciousness. Such a conclusion must reflect the main characteristics of the EEG, and includes three mandatory parts:
Decoding the electroencephalogram involves interpreting the conclusion. Let's consider the basic concepts that the doctor reflects in the conclusion and their clinical significance (that is, what these or those parameters can indicate). High frequency and instability of the alpha rhythm indicate traumatic brain damage, for example, after a concussion or traumatic brain injury. Disorganization of the alpha rhythm or its complete absence indicates acquired dementia. About delayed psycho-motor development in children they say:
Excitable psychopathy is manifested by a slowdown in the frequency of the alpha rhythm against the background of normal synchrony. Inhibitory psychopathy is manifested by EEG desynchronization, low frequency and alpha rhythm index. Increased synchronization of the alpha rhythm in all parts of the brain, a short activation reaction - the first type of neuroses. Weak expression of the alpha rhythm, weak activation reactions, paroxysmal activity - the third type of neuroses. Short spindles in the beta rhythm indicate encephalitis. The more severe the inflammation of the brain, the greater the frequency, duration and amplitude of such spindles. Observed in a third of patients with herpes encephalitis. Beta waves with a frequency of 16–18 Hz and high amplitude (30–40 μV) in the anterior and central parts of the brain are signs of delayed psychomotor development of a child. EEG desynchronization, in which the beta rhythm predominates in all parts of the brain, is the second type of neurosis. In children and young people under 21 years of age, the electroencephalogram may reveal diffuse theta and delta rhythms, paroxysmal discharges and epileptoid activity, which are normal variants and do not indicate pathological changes in brain structures. Synchronous theta rhythm, delta waves in all parts of the brain, bursts of bilateral synchronous theta waves with high amplitude, paroxysms in the central parts of the brain - indicate acquired dementia. The predominance of theta and delta waves on the EEG with maximum activity in the occipital region, flashes of bilateral synchronous waves, the number of which increases with hyperventilation, indicates a delay in the psychomotor development of the child. A high index of theta activity in the central parts of the brain, bilateral synchronous theta activity with a frequency of 5 to 7 Hz, localized in the frontal or temporal regions of the brain indicate psychopathy. Theta rhythms in the anterior parts of the brain as the main ones are an excitable type of psychopathy. Paroxysms of theta and delta waves are the third type of neuroses. The appearance of high-frequency rhythms (for example, beta-1, beta-2 and gamma) indicates irritation (irritation) of brain structures. This may be due to various cerebrovascular accidents, intracranial pressure, migraines, etc. What do various disturbances in the bioelectrical activity of the brain indicate? Diffuse changes in the bioelectrical activity of the brain may be normal if no other abnormalities are detected. Thus, if in the conclusion it is written only about diffuse or moderate changes in the bioelectrical activity of the brain, without paroxysms, foci of pathological activity, or without a decrease in the threshold of convulsive activity, then this is a variant of the norm. In this case, the neurologist will prescribe symptomatic treatment and put the patient under observation. However, in combination with paroxysms or foci of pathological activity, they speak of the presence of epilepsy or a tendency to seizures. Reduced bioelectrical activity of the brain can be detected in depression. Interhemispheric asymmetry
may be a functional disorder, that is, not indicate pathology. In this case, it is necessary to undergo examination by a neurologist and a course of symptomatic therapy. Diffuse disorganization of the alpha rhythm, activation of diencephalic-stem structures of the brain
against the background of tests (hyperventilation, closing-opening of eyes, photostimulation) is the norm, if the patient has no complaints. Center of pathological activity
indicates increased excitability of this area, which indicates a tendency to seizures or the presence of epilepsy. Irritation of various brain structures
(cortex, middle sections, etc.) is most often associated with impaired cerebral circulation due to various reasons (for example, atherosclerosis, trauma, increased intracranial pressure, etc.). Paroxysms They talk about increased excitation and decreased inhibition, which is often accompanied by migraines and simple headaches. In addition, there may be a tendency to develop epilepsy or the presence of this pathology if a person has had seizures in the past. Reducing the threshold for seizure activity
indicates a predisposition to seizures. The following signs indicate the presence of increased excitability and a tendency to convulsions: Irritation of the cerebral cortex along the convexial surface of the brain, increased activity of the median structures
at rest and during tests can be observed after traumatic brain injuries, with a predominance of excitation over inhibition, as well as with organic pathology of brain tissue (for example, tumors, cysts, scars, etc.). Epileptiform activity
indicates the development of epilepsy and an increased tendency to seizures. Increased tone of synchronizing structures and moderate dysrhythmia
are not pronounced disorders or pathologies of the brain. In this case, resort to symptomatic treatment. Signs of neurophysiological immaturity
may indicate a delay in the child’s psychomotor development. Pronounced changes in residual organic type
with increasing disorganization during tests, paroxysms in all parts of the brain - these signs usually accompany severe headaches, increased intracranial pressure, attention deficit hyperactivity disorder in children. Disturbance of brain wave activity
(appearance of beta activity in all parts of the brain, dysfunction of midline structures, theta waves) occurs after traumatic injuries, and can manifest itself as dizziness, loss of consciousness, etc. Organic changes in brain structures
in children are a consequence of infectious diseases such as cytomegalovirus or toxoplasmosis, or hypoxic disorders that occur during childbirth. A comprehensive examination and treatment is necessary. Regulatory cerebral changes
are registered in hypertension. The presence of active discharges in any part of the brain
, which intensify with exercise, means that in response to physical stress a reaction may develop in the form of loss of consciousness, visual impairment, hearing loss, etc. The specific reaction to physical activity depends on the location of the source of active discharges. In this case, physical activity should be limited to reasonable limits. In case of brain tumors, the following are detected: Desynchronization of rhythms, flattening of the EEG curve
develops in cerebrovascular pathologies. A stroke is accompanied by the development of theta and delta rhythms. The degree of electroencephalogram abnormalities correlates with the severity of the pathology and the stage of its development. Theta and delta waves in all parts of the brain; in some areas, beta rhythms are formed during injury (for example, with a concussion, loss of consciousness, bruise, hematoma). The appearance of epileptoid activity against the background of brain injury can lead to the development of epilepsy in the future. It is known that in a healthy person, the pattern of bioelectrical activity of the brain, reflecting its morpho-functional state, is directly determined by the age period and, therefore, each of them has its own characteristics. The most intense processes associated with the development of the structure and functional improvement of the brain occur in childhood, which is expressed in the most significant changes in the qualitative and quantitative indicators of the electroencephalogram during this period of ontogenesis. 2.1. Peculiarities of children's EEG in a state of quiet wakefulness Electroencephalogram of a newborn full-term baby in a state of wakefulness, it is polymorphic with the absence of organized rhythmic activity and is represented by generalized irregular low-amplitude (up to 20 μV) slow waves of predominantly delta range with a frequency of 1–3 beats/s. without regional differences and clear symmetry [Farber D. A., 1969, Zenkov L. R., 1996]. The greatest amplitude of patterns is possible in the central [Posikera I.N., Stroganova T.A., 1982] or in the parieto-occipital regions of the cortex; episodic series of irregular alpha oscillations with an amplitude of up to 50–70 μV can be observed (Fig. 2.1). TO 1-2,5
months, in children the amplitude of biopotentials increases to 50 μV, rhythmic activity with a frequency of 4-6 beats/s may be noted in the occipital and central regions. The predominant delta waves acquire a bilateral synchronous organization (Fig. 2.2). WITH 3
-months of age, a mu rhythm can be detected in the central regions with a frequency varying in the range of 6–10 counts/s (the frequency mode of the mu rhythm is 6.5 counts/s), with an amplitude of up to 20–50 μV, sometimes with moderate interhemispheric asymmetry . WITH 3-4
months, a rhythm with a frequency of about 4 beats/s is recorded in the occipital regions, responding to the opening of the eyes. In general, the EEG continues to remain unstable with the presence of oscillations of different frequencies (Fig. 2.3). TO 4
months, children experience diffuse delta and theta activity; rhythmic activity with a frequency of 6–8 beats/s can be present in the occipital and central regions. WITH 6th month, the rhythm of 5–6 beats/s dominates on the EEG [Blagosklonova N.K., Novikova L.A., 1994] (Fig. 2.4). According to T.A. Stroganova et al. (2005) the average peak frequency of alpha activity at 8 months of age is 6.24 counts/s, and at 11 months of age - 6.78 counts/s. The frequency mode of the mu rhythm in the period from 5–6 months to 10–12 months is 7 counts/s and 8 counts/s after 10–12 months. Electroencephalogram of a child aged 1 year characterized by sinusoidal oscillations of alpha-like activity (alpha activity is an ontogenetic variant of the alpha rhythm) expressed in all recorded areas with a frequency of 5 to 7, less often 8–8.5 counts/sec, interspersed with individual waves of the highest frequency and diffuse delta waves [Farber D.A., Alferova V.V., 1972; Zenkov L.R., 1996]. Alpha activity is unstable and, despite its wide regional representation, as a rule, does not exceed 17–20% of the total recording time. The main share belongs to the theta rhythm - 22–38%, as well as the delta rhythm - 45–61%, on which alpha and theta oscillations can be superimposed. The amplitude values of the main rhythms in children up to 7 years old vary in the following ranges: the amplitude of alpha activity - from 50 µV to 125 µV, theta-rhythm - from 50 µV to 110 µV, delta rhythm - from 60 µV to 100 µV [Koroleva N.V., Kolesnikov S.I., 2005] (Fig. 2.5). At the age of 2 years alpha activity is also present in all areas, although its severity decreases towards the anterior parts of the cerebral cortex. Alpha oscillations have a frequency of 6–8 counts/sec and are interspersed with groups of high-amplitude oscillations with a frequency of 2.5–4 counts/sec. In all recorded areas, the presence of beta waves with a frequency of 18–25 counts/sec can be noted [Farber D. A., Alferova V. V., 1972; Blagosklonova N.K., Novikova L.A., 1994; Koroleva N.V., Kolesnikov S.I., 2005]. The values of the indices of the main rhythms at this age are close to those in one-year-old children (Fig. 2.6). Starting from 2 years of age, EEG in children in the series of alpha activity, more often in the parieto-occipital region, can reveal polyphasic potentials, which are a combination of an alpha wave with a preceding or following slow wave. Polyphasic potentials can be bilaterally synchronous, somewhat asymmetrical, or predominate alternately in one of the hemispheres [Blagosklonova N.K., Novikova L.A., 1994]. Electroencephalogram of a 3–4 year old child theta range oscillations dominate. At the same time, the alpha activity predominant in the occipital leads continues to be combined with a significant number of high-amplitude slow waves with a frequency of 2–3 counts/sec and 4–6 counts/sec [Zislina N.N., Tyukov V.L., 1968]. The alpha activity index at this age ranges from 22–33%, the theta rhythm index is 23–34%, and the representation of the delta rhythm decreases to 30–45%. The frequency of alpha activity averages 7.5–8.4 counts/sec, varying from 7 to 9 counts/sec. That is, during this age period, a focus of alpha activity appears with a frequency of 8 counts/sec. At the same time, the frequency of oscillations of the theta spectrum also increases [Farber D. A., Alferova V. V., 1972; Koroleva N.V., Kolesnikov S.I., 2005 Normal..., 2006]. Alpha activity has the greatest amplitude in the parieto-occipital regions and can take on a pointed shape (Fig. 2.7). In children up to 10-12 years of age, the electroencephalogram against the background of basic activity can reveal high-amplitude bilaterally synchronous bursts of oscillations with a frequency of 2-3 and 4-7 counts/sec, predominantly expressed in the fronto-central, central-parietal or parieto-occipital areas of the cerebral cortex, or having a generalized nature without a pronounced accent. In practice, these paroxysms are regarded as signs of hyperactivity of the brain stem structures. The noted paroxysms most often occur during hyperventilation (Fig. 2.22, Fig. 2.23, Fig. 2.24, Fig. 2.25). At 5-6 years of age on the electroencephalogram The organization of the basic rhythm increases and activity is established with the frequency of the alpha rhythm characteristic of adults. The alpha activity index is more than 27%, the theta index is 20–35%, and the delta index is 24–37%. Slow rhythms have a diffuse distribution and do not exceed in amplitude alpha activity, which predominates in amplitude and index in the parieto-occipital regions. The frequency of alpha activity within one recording can vary from 7.5 to 10.2 counts/sec, but its average frequency is 8 or more counts/sec (Fig. 2.8). In electroencephalograms of 7-9 year olds In children, the alpha rhythm is represented in all areas, but its greatest severity is characteristic of the parieto-occipital areas. The record is dominated by alpha and theta rites, the index of slower activity does not exceed 35%. The alpha index varies between 35–55%, and the theta index - between 15–45%. The beta rhythm is expressed in the form of groups of waves and is recorded diffusely or with an emphasis in the frontotemporal areas, with a frequency of 15–35 counts/sec, and an amplitude of up to 15–20 μV. Among the slow rhythms, oscillations with a frequency of 2–3 and 5–7 counts/sec predominate. The predominant frequency of the alpha rhythm at this age is 9–10 counts/sec and has its highest values in the occipital areas. The amplitude of the alpha rhythm varies from 70 to 110 μV in different individuals; slow waves may have the greatest amplitude in the parietal-posterior-temporal-occipital regions, which is always lower than the amplitude of the alpha rhythm. Closer to 9 years of age, unclear modulations of the alpha rhythm may appear in the occipital regions (Fig. 2.9). In electroencephalograms of children 10–12 years old Alpha rhythm maturation is largely complete. The recording shows an organized, well-defined alpha rhythm, dominating in terms of recording time over the other main rhythms and accounting for 45–60% in terms of the index. In terms of amplitude, the alpha rhythm predominates in the parieto-occipital or posterior-temporal-parieto-occipital regions, where alpha oscillations can also be grouped into individual modulations that are not yet clearly defined. The frequency of the alpha rhythm varies between 9–11 counts/sec and more often fluctuates around 10 counts/sec. In the anterior sections, the alpha rhythm is less organized and uniform, and also noticeably lower in amplitude. Against the background of the dominant alpha rhythm, single theta waves are detected with a frequency of 5–7 counts/sec and an amplitude not exceeding other EEG components. Also, from the age of 10 years, there is an increase in beta activity in the frontal leads. Bilateral generalized outbreaks of paroxysmal activity from this stage of ontogenesis in adolescents are normally no longer recorded [Blagosklonova N.K., Novikova L.A., 1994; Sokolovskaya I.E., 2001] (Fig. 2.10). EEG of adolescents aged 13–16 years characterized by ongoing processes of formation of bioelectrical activity of the brain. The alpha rhythm becomes the dominant form of activity and predominates in all areas of the cortex, the average frequency of the alpha rhythm is 10–10.5 counts/sec [Sokolovskaya I. E., 2001]. In some cases, along with a fairly pronounced alpha rhythm in the occipital regions, there may be less stability in the parietal, central and frontal areas of the cortex and its combination with low-amplitude slow waves. During this age period, the greatest degree of similarity of the alpha rhythm of the occipital-parietal and central-frontal areas of the cortex is established, reflecting an increase in the attunement of various areas of the cortex in the process of ontogenesis. The amplitudes of the basic rhythms also decrease, approaching those in adults, and there is a decrease in the sharpness of regional differences in the basic rhythm in comparison with young children (Fig. 2.11). After 15 years, in adolescents, polyphasic potentials gradually disappear on the EEG, occasionally occurring in the form of single oscillations; sinusoidal rhythmic slow waves with a frequency of 2.5–4.5 counts/sec cease to be recorded; the severity of low-amplitude slow oscillations in the central areas of the cortex decreases. The EEG reaches the full degree of maturity characteristic of adults by the age of 18–22 [Blagosklonova N.K., Novikova L.A., 1994]. 2.2. Changes in children's EEG under functional loads When analyzing the functional state of the brain, it is important to evaluate the nature of its bioelectrical activity not only in a state of quiet wakefulness, but also its changes during functional loads. The most common of them are: test with opening-closing eyes, test with rhythmic photostimulation, hyperventilation, sleep deprivation. An eye opening-closing test is necessary to assess the reactivity of the bioelectrical activity of the brain. When the eyes open, there is a generalized suppression and decrease in the amplitude of alpha activity and slow-wave activity, representing an activation response. During the activation reaction, a mu rhythm with a frequency of 8-10 counts/sec and an amplitude not exceeding alpha activity can be maintained in the central areas bilaterally. When you close your eyes, alpha activity increases. The activation reaction is carried out due to the activating influence of the reticular formation of the midbrain and depends on the maturity and safety of the neural apparatus of the cerebral cortex. Already during the newborn period, in response to a flash of light, EEG flattening is noted [Farber D.A., 1969; Beteleva T.G. et al., 1977; Westmoreland B. Stockard J., 1977; Coen R.W., Tharp B.R., 1985]. However, in young children the activation reaction is poorly expressed and its severity improves with age (Fig. 2.12). In a state of quiet wakefulness, the activation reaction begins to manifest itself more clearly from 2-3 months of age [Farber D.A., 1969] (Fig. 2.13). Children aged 1–2 years have a weakly expressed (75-95% preservation of the background amplitude level) activation reaction (Fig. 2.14). In the period of 3–6 years, the frequency of occurrence of a fairly pronounced (50–70% preservation of the background amplitude level) activation reaction increases and its index increases, and from the age of 7, all children register an activation reaction amounting to 70% or less preservation of the background amplitude level of the EEG ( Fig. 2.15). By the age of 13, the activation reaction stabilizes and approaches the typical adult type, expressed in the form of desynchronization of cortical rhythms [Farber D.A., Alferova V.V., 1972] (Fig. 2.16). A test with rhythmic photostimulation is used to assess the nature of the brain's response to external influences. Also, rhythmic photostimulation is often used to provoke pathological EEG activity. A typical response to rhythmic photostimulation is normally the reaction of assimilation (imposition, following) of rhythm - the ability of EEG oscillations to repeat the rhythm of light flickers with a frequency equal to the frequency of light flashes (Fig. 2.17) in harmonics (with the transformation of rhythms towards high frequencies, multiples of the frequency of light flashes ) or subharmonic (with transformation of rhythms towards low frequencies, multiples of the frequency of light flashes) (Fig. 2.18). In healthy subjects, the reaction of rhythm assimilation is most clearly expressed at frequencies close to the frequencies of alpha activity; it is maximally and symmetrically manifested in the occipital regions of the hemispheres [Blagosklonova N.K., Novikova L.A., 1994; Zenkov L.R., 1996], although in children its more generalized expression is possible (Fig. 2.19). Normally, the rhythm assimilation reaction stops no later than 0.2–0.5 s after the end of photostimulation [Zenkov L.R., Ronkin M.A., 1991]. The reaction of rhythm assimilation, as well as the activation reaction, depends on the maturity and preservation of cortical neurons and the intensity of the impact of nonspecific brain structures of the mesodiencephalic level on the cerebral cortex. The rhythm assimilation reaction begins to be recorded from the neonatal period and is predominantly represented in the frequency range from 2 to 5 beats/s [Blagosklonova N.K., Novikova L.A., 1994]. The range of assimilated frequencies correlates with the frequency of alpha activity that changes with age. In children 1–2 years old, the range of assimilated frequencies is 4–8 counts/sec. At preschool age, the assimilation of the rhythm of light flickers is observed in the range of theta frequencies and alpha frequencies; from 7–9 in children, the optimal assimilation of the rhythm moves to the range of the alpha rhythm [Zislina N.N., 1955; Novikova L.A., 1961], and in older children - in the range of alpha and beta rhythms. A test with hyperventilation, like a test with rhythmic photostimulation, can enhance or provoke pathological brain activity. EEG changes during hyperventilation are caused by cerebral hypoxia caused by reflex spasm of arterioles and a decrease in cerebral blood flow in response to a decrease in the concentration of carbon dioxide in the blood. Because cerebral vascular reactivity decreases with age, the drop in oxygen saturation during hyperventilation is more pronounced before the age of 35. This causes significant changes in the EEG during hyperventilation at a young age [Blagosklonova N.K., Novikova L.A., 1994]. Thus, in children of preschool and primary school age, with hyperventilation, the amplitude and index of slow activity can significantly increase with possible complete replacement of alpha activity (Fig. 2.20, Fig. 2.21). In addition, at this age, during hyperventilation, bilaterally synchronous flashes and periods of high-amplitude oscillations with a frequency of 2–3 and 4–7 counts/sec may appear, predominantly expressed in the central-parietal, parieto-occipital or central-frontal areas of the cerebral cortex [Blagosklonova N .K., Novikova L.A., 1994; Blume W.T., 1982; Sokolovskaya I.E., 2001] (Fig. 2.22, Fig. 2.23) or having a generalized nature without a pronounced accent and caused by increased activity of the mid-stem structures (Fig. 2.24, Fig. 2.25). After 12–13 years, the reaction to hyperventilation gradually becomes less pronounced; there may be a slight decrease in the stability, organization and frequency of the alpha rhythm, a slight increase in the amplitude of the alpha rhythm and the index of slow rhythms (Fig. 2.26). Bilateral generalized outbreaks of paroxysmal activity from this stage of ontogenesis, as a rule, are no longer normally recorded. Normally, EEG changes after hyperventilation last no more than 1 minute [Blagosklonova N.K., Novikova L.A., 1994]. The sleep deprivation test consists of reducing the duration of sleep compared to physiological sleep and helps to reduce the level of activation of the cerebral cortex by nonspecific activating systems of the brain stem. A decrease in the level of activation and an increase in excitability of the cerebral cortex in patients with epilepsy contributes to the manifestation of epileptiform activity, mainly in idiopathic generalized forms of epilepsy (Fig. 2.27a, Fig. 2.27b) The most powerful way to activate epileptiform changes is to register EEG sleep after its preliminary deprivation [Blagosklonova N.K., Novikova L.A., 1994; Chlorpromazine..., 1994; Foldvary-Schaefer N., Grigg-Damberger M., 2006]. 2.3.Features of children's EEG during sleep Sleep has long been considered a powerful activator of epileptiform activity. It is known that epileptiform activity is observed mainly in stages I and II of slow-wave sleep. A number of authors have noted that slow-wave sleep selectively facilitates the occurrence of generalized paroxysms, and rapid sleep - local and especially temporal ones. As is known, the slow and fast phases of sleep correlate with the activity of various physiological mechanisms, and there is a connection between the electroencephalographic phenomena recorded during these phases of sleep and the activity of the cortex and subcortical formations of the brain. The main synchronizing system responsible for the slow-wave sleep phase is the thalamo-cortical system. Structures of the brain stem, mainly the pons, are involved in the organization of REM sleep, which is characterized by desynchronizing processes. In addition, in young children it is more appropriate to assess bioelectrical activity in a state of sleep, not only because during this age period the recording during wakefulness is distorted by motor and muscle artifacts, but also due to its insufficient information content due to the unformation of the basic cortical rhythm. At the same time, the age-related dynamics of bioelectrical activity in the sleep state is much more intense and already in the first months of life, all the basic rhythms characteristic of an adult in this state are observed on the child’s sleep electroencephalogram. It should be noted that to identify the phases and stages of sleep, an electrooculogram and electromyogram are recorded simultaneously with the EEG. Normal human sleep consists of alternating a series of cycles of slow-wave sleep (non-REM sleep) and rapid sleep (REM sleep). Although in a newborn full-term child, undifferentiated sleep can also be identified, when it is impossible to clearly distinguish between the phases of fast and slow sleep. During the REM sleep phase, sucking movements are often observed, almost continuous body movements, smiles, grimaces, slight tremors, and vocalizations are noted. Simultaneously with the phasic movements of the eyeballs, bursts of muscle movements and irregular breathing are observed. The slow-wave sleep phase is characterized by minimal physical activity. The onset of sleep in newborn children is marked by the onset of the REM sleep phase, which on the EEG is characterized by low-amplitude oscillations of various frequencies, and sometimes low synchronized theta activity [Blagosklonova N.K., Novikova L.A., 1994; Stroganova T.A. et al., 2005] (Fig. 2.28). At the beginning of the slow-wave sleep phase, sinusoidal oscillations in the theta range with a frequency of 4–6 counts/s and an amplitude of up to 50 μV, more pronounced in the occipital leads, and/or generalized bursts of high-amplitude slow activity may appear on the EEG. The latter can persist until 2 years of age [Farber D.A., Alferova V.V., 1972] (Fig. 2.29). As sleep deepens in newborns, the EEG acquires an alternating character - high-amplitude (from 50 to 200 μV) bursts of delta oscillations with a frequency of 1–4 beats/s occur, combined with rhythmic low-amplitude theta waves with a frequency of 5–6 beats/s, alternating with periods of suppression of bioelectrical activity, represented by continuous low-amplitude (from 20 to 40 μV) activity. These flashes lasting 2–4 s occur every 4–5 s [Blagosklonova N.K., Novikova L.A., 1994; Stroganova T.A. et al., 2005] (Fig. 2.30). During the neonatal period, frontal sharp waves, bursts of multifocal sharp waves and beta-delta complexes (“delta-beta brushes”) can also be recorded during the slow-wave sleep phase. Frontal sharp waves are biphasic sharp waves with a primary positive component, followed by a negative component with an amplitude of 50–150 μV (sometimes up to 250 μV) and are often associated with frontal delta activity [Stroganova T. A. et al., 2005] ( Fig. 2.31). Beta-delta complexes - graphelements consisting of delta waves with a frequency of 0.3–1.5 counts/s, amplitude up to 50–250 μV, combined with fast activity, frequency 8–12, 16–22 counts/s, amplitude up to 75 µV. Bate-delta complexes arise in the central and/or temporo-occipital regions and, as a rule, are bilaterally asynchronous and asymmetrical (Fig. 2.32). By the age of one month, the alternation disappears on the EEG of slow sleep, delta activity is continuous and at the beginning of the slow sleep phase can be combined with faster oscillations (Fig. 2.33). Against the background of the presented activity, periods of bilateral synchronous theta activity with a frequency of 4–6 counts/s and an amplitude of up to 50–60 μV may occur (Fig. 2.34). As sleep deepens, delta activity increases in amplitude and index and is presented in the form of high-amplitude oscillations up to 100–250 μV, with a frequency of 1.5–3 counts/s; theta activity, as a rule, has a low index and is expressed in the form of diffuse oscillations ; slow-wave activity usually dominates in the posterior parts of the hemispheres (Fig. 2.35). Starting from 1.5–2 months of life, bilaterally synchronous and/or asymmetrically expressed “sleep spindles” (sigma rhythm) appear on the EEG of slow-wave sleep in the central parts of the hemispheres, which are periodically occurring spindle-shaped rhythmic groups of oscillations that increase and decrease in amplitude frequency 11–16 counts/s, amplitude up to 20 μV [Fantalova V.L. et al., 1976]. “Sleep spindles” at this age are still rare and short in duration, but by 3 months of age they increase in amplitude (up to 30-50 μV) and duration. It should be noted that up to 5 months of age, “sleep spindles” may not have a fusiform shape and manifest themselves in the form of continuous activity lasting up to 10 s or more. Amplitude asymmetry of “sleep spindles” of more than 50% is possible [Stroganova T.A. et al., 2005]. "Sleepy spindles" combined with polymorphic bioelectrical activity, sometimes preceded by K-complexes or vertex potentials (Fig. 2.36) K-complexes are bilaterally synchronous, predominantly expressed in the central region, biphasic sharp waves, in which the negative acute potential is accompanied by a slow positive deflection. K-complexes can be induced on the EEG by presentation of an auditory stimulus without awakening the subject. K-complexes have an amplitude of at least 75 μV, and, like vertex potentials, may not always be distinct in young children (Fig. 2.37). Vertex potentials (V -wave) is a single or biphasic sharp wave often accompanied by a slow wave of opposite polarity, that is, the initial phase of the pattern has a negative deflection, followed by a low amplitude positive phase, and then a slow wave with a negative deflection. Vertex potentials have a maximum amplitude (usually no more than 200 μV) in the central leads and can have an amplitude asymmetry of up to 20% while maintaining their bilateral synchronization (Fig. 2.38). During shallow slow-wave sleep, bursts of generalized bilaterally synchronous polyphasic slow waves can be recorded (Fig. 2.39). As slow-wave sleep deepens, “sleep spindles” become less frequent (Fig. 2.40) and in deep slow-wave sleep, characterized by high-amplitude slow activity, usually disappear (Fig. 2.41). From 3 months of life, a child’s sleep always begins with the slow-wave sleep phase [Stroganova T.A. et al., 2005]. On the EEG of children 3–4 months old, regular theta activity with a frequency of 4–5 counts/s and an amplitude of up to 50–70 μV is often noted upon the onset of slow-wave sleep, manifesting mainly in the central-parietal regions. From 5 months of age, the EEG begins to differentiate stage I sleep (drowsiness), characterized by a “rhythm of falling asleep,” expressed in the form of generalized high-amplitude hypersynchronous slow activity with a frequency of 2–6 beats/s, amplitude from 100 to 250 μV. This rhythm manifests itself persistently throughout the 1st–2nd year of life (Fig. 2.42). When transitioning to shallow sleep, there is a reduction in the “rhythm of falling asleep” and the amplitude of background bioelectrical activity decreases. In children 1–2 years old, at this time groups of beta rhythms with an amplitude of up to 30 μV and a frequency of 18–22 beats/s can also be observed, often dominant in the posterior parts of the hemispheres. According to S. Guilleminault (1987), the slow-wave sleep phase can be divided into four stages, into which slow-wave sleep in adults is divided, already at the age of 8–12 weeks of life. However, the sleep pattern most similar to adults is still observed at older ages. In older children and adults, the onset of sleep is marked by the onset of the slow-wave sleep phase, which, as noted above, is divided into four stages. Stage I sleep (drowsiness) characterized by a polymorphic, low-amplitude curve with diffuse theta-delta oscillations and low-amplitude high-frequency activity. The activity of the alpha range can be presented in the form of single waves (Fig. 2.43a, Fig. 2.43b) The presentation of external stimuli can cause the appearance of bursts of high-amplitude alpha activity [Zenkov L.R., 1996] (Fig. 2.44) At this stage the appearance of vertex potentials is also noted, maximally expressed in the central sections, which can occur in stages II and III of sleep (Fig. 2.45). Periodic rhythmic high-amplitude slow activity with a frequency of 4–6 Hz may be observed in the frontal leads. In children at this stage, generalized bilaterally synchronous bursts of theta waves may appear (Fig. 2.46), bilaterally synchronous with the greatest severity in the frontal leads of flashes of slow waves with a frequency of 2–4 Hz, amplitude from 100 to 350 μV. In their structure, a spike-like component can be noted. IN I-II stages Flashes of arc-shaped electropositive spikes or sharp waves may occur with a frequency of 14 and (or) 6-7 counts/s lasting from 0.5 to 1 second. monolaterally or bilaterally asynchronously with the greatest severity in the posterior temporal leads (Fig. 2.47). Also, in stages I-II of sleep, transient positive sharp waves in the occipital leads (POSTs) may occur - periods of high-amplitude bilaterally synchronous (often with pronounced (up to 60%) asymmetry of patterns) mono- or diphasic waves with a frequency of 4-5 counts/ s, represented by a positive initial phase of the pattern, followed by possible accompaniment by a low-amplitude negative wave in the occipital regions. During the transition to stage III, “positive occipital sharp waves” slow down to 3 beats/s and below (Fig. 2.48). The first stage of sleep is characterized by slow eye movement. Stage II sleep identified by the appearance on the EEG of generalized “sleep spindles” (sigma rhythm) and K-complexes with a predominance in the central sections. In older children and adults, the amplitude of “sleep spindles” is 50 μV, and the duration ranges from 0.5 to 2 seconds. The frequency of “sleep spindles” in the central regions is 12–16 counts/s, and in the frontal areas - 10–12 counts/s. At this stage, outbreaks of polyphase high-amplitude slow waves are occasionally observed [Zenkov L.R., 1996] (Fig. 2.49). Stage III sleep characterized by an increase in EEG amplitude (more than 75 μV) and the number of slow waves, mainly in the delta range. K-complexes and sleep spindles are recorded. Delta waves with a frequency of no higher than 2 counts/s during the epoch of EEG analysis occupy from 20 to 50% of the recording [Vein A.M., Hecht K, 1989]. There is a decrease in the beta activity index (Fig. 2.50). Stage IV sleep characterized by the disappearance of “sleep spindles” and K-complexes, the appearance of high-amplitude (more than 75 μV) delta waves with a frequency of 2 counts/s or less, which at the time of EEG analysis constitute more than 50% of the recording [Vein A.M., Hecht K, 1989 ]. Stages III and IV of sleep are the deepest sleep and are combined under the general name “delta sleep” (“slow wave sleep”) (Fig. 2.51). The REM sleep phase is characterized by the appearance on the EEG of desynchronization in the form of irregular activity with single low-amplitude theta waves, rare groups of slow alpha rhythm and “sawtooth activity”, which is bursts of slow sharp waves with a frequency of 2–3 beats/s, the ascending front of which is superimposed an additional pointed wave, giving them a two-pronged character [Zenkov L.R., 1996]. The REM sleep phase is accompanied by rapid movements of the eyeballs and a diffuse decrease in muscle tone. It is during this phase of sleep that dreams occur in healthy people (Fig. 2.52). During the period of awakening in children, a “frontal rhythm of awakening” may appear on the EEG, presented in the form of rhythmic paroxysmal island-wave activity with a frequency of 7–10 beats/s, lasting up to 20 seconds in the frontal leads. The phases of slow and fast sleep alternate throughout the entire sleep period, however, the total duration of sleep cycles differs at different age periods: in children under 2–3 years old it is about 45–60 minutes, by 4–5 years it increases to 60–90 minutes, for older children - 75–100 minutes. In adults, the sleep cycle lasts 90–120 minutes and 4 to 6 sleep cycles occur per night. The duration of sleep phases also has an age dependence: in infants, the REM sleep phase can occupy up to 60% of the time of the sleep cycle, and in adults - up to 20–25% [Gecht K., 2003]. Other authors note that in full-term newborns, REM sleep occupies at least 55% of the time of the sleep cycle, in children of one month of age - up to 35%, at 6 months of age - up to 30%, and by 1 year - up to 25% of the time of the sleep cycle [Stroganova T.A. et al., 2005], In general, in older children and adults, stage I sleep lasts from 30 seconds. up to 10–15 minutes, stage II - from 30 to 60 minutes, stages III and IV - 15–30 minutes, REM sleep phase - 15–30 minutes. Up to 5 years, periods of REM sleep during sleep are characterized by equal duration. Subsequently, the uniformity of REM episodes throughout the night disappears: the first REM episode becomes short, while subsequent ones increase in duration as they approach the early morning hours. By the age of 5, the ratio between the percentage of time falling on the slow-wave sleep phase and the REM sleep phase is achieved, practically characteristic of adults: in the first half of the night, slow-wave sleep is most clearly expressed, and in the second, episodes of the REM sleep phases become the longest. 2.4. Non-epileptiform paroxysms of children's EEG The issue of identifying non-epileptiform paroxysms on the EEG is one of the key issues in the differential diagnosis of epileptic and non-epileptic conditions, especially in childhood, when the frequency of various EEG paroxysms is significantly high. Based on the well-known definition, paroxysm is a group of oscillations that differ sharply in structure, frequency, amplitude from background activity, suddenly appearing and disappearing. Paroxysms include flashes and discharges - paroxysms of non-epileptiform and epileptiform activity, respectively. Non-epileptiform paroxysmal activity in children includes the following patterns: Among non-epileptiform paroxysmal activity, “conditional epileptiform” activity is also distinguished, which has diagnostic value only in the presence of an appropriate clinical picture. “Conditionally epileptiform” paroxysmal activity includes:13.2. Electrophysiological methods for studying the dynamics of mental development
13.2.1. Changes in the electroencephalogram during ontogenesis
"
The bridge in a newborn is located higher compared to its position in an adult, and by the age of 5 it is located at the same level as in an adult. The development of the pons is associated with the formation of the cerebellar peduncles and the establishment of connections between the cerebellum and other parts of the central nervous system. The internal structure of the bridge in a child has no distinctive features compared to its structure in an adult. The nuclei of the nerves located in it are formed by the period of birth.Electroencephalogram of the brain - definition and essence of the method
Electroencephalogram (EEG) is a recording of the electrical activity of neurons in various brain structures, which is made on special paper using electrodes. Electrodes are placed on different parts of the head and record the activity of a particular part of the brain. We can say that an electroencephalogram is a recording of the functional activity of the brain of a person of any age.
1.
Photostimulation (exposure to flashes of bright light on closed eyes).
2.
Opening and closing eyes.
3.
Hyperventilation (rare and deep breathing for 3 to 5 minutes).
Additional tests for EEG are determined by a neurologist who wants to evaluate certain functions of a person's brain. What does an electroencephalogram show?
An electroencephalogram reflects the functional state of brain structures in various human states, for example, sleep, wakefulness, active mental or physical work, etc. An electroencephalogram is an absolutely safe method, simple, painless and does not require serious intervention. Where and how to do it?
An electroencephalogram for an adult can be taken in neurological clinics, in departments of city and regional hospitals, or at a psychiatric clinic. As a rule, electroencephalograms are not taken in clinics, but there are exceptions to the rule. It is better to go to a psychiatric hospital or neurology department, where specialists with the necessary qualifications work. Electroencephalogram for children: how the procedure is performed
Taking an electroencephalogram in children often raises questions from parents who want to know what awaits the baby and how the procedure goes. The child is left in a dark, sound- and light-proof room, where he is placed on a couch. Children under 1 year of age are kept in their mother's arms during EEG recording. The whole procedure takes about 20 minutes. Electroencephalogram rhythms
The electroencephalogram must show a regular rhythm of a certain type. The regularity of rhythms is ensured by the work of the part of the brain - the thalamus, which generates them and ensures the synchronization of the activity and functional activity of all structures of the central nervous system. Electroencephalogram results
The result of the electroencephalogram is a recording on paper or in computer memory. The curves are recorded on paper and analyzed by the doctor. The rhythm of EEG waves, frequency and amplitude are assessed, characteristic elements are identified, and their distribution in space and time is recorded. Then all the data is summarized and reflected in the conclusion and description of the EEG, which is pasted into the medical record. The EEG conclusion is based on the type of curves, taking into account the clinical symptoms present in a person.
1.
Description of the activity and typical affiliation of EEG waves (for example: “The alpha rhythm is recorded over both hemispheres. The average amplitude is 57 μV on the left and 59 μV on the right. The dominant frequency is 8.7 Hz. The alpha rhythm dominates in the occipital leads.”).
2.
Conclusion according to the description of the EEG and its interpretation (for example: “Signs of irritation of the cortex and midline structures of the brain. Asymmetry between the hemispheres of the brain and paroxysmal activity were not detected”).
3.
Determining the correspondence of clinical symptoms with EEG results (for example: “Objective changes in the functional activity of the brain were recorded, corresponding to manifestations of epilepsy”).Decoding the electroencephalogram
Decoding an electroencephalogram is the process of interpreting it taking into account the clinical symptoms present in the patient. In the process of decoding, it is necessary to take into account the basal rhythm, the level of symmetry in the electrical activity of brain neurons of the left and right hemispheres, the activity of the commissure, EEG changes against the background of functional tests (opening - closing the eyes, hyperventilation, photostimulation). The final diagnosis is made only taking into account the presence of certain clinical signs that concern the patient. Alpha - rhythm
Normally, its frequency is 8–13 Hz, the amplitude ranges up to 100 μV. It is this rhythm that should prevail over both hemispheres in healthy adults. Alpha rhythm pathologies are the following:
What do common alpha rhythm disturbances indicate?
Severe interhemispheric asymmetry may indicate the presence of a brain tumor, cyst, stroke, heart attack or scar at the site of an old hemorrhage.
A decrease in the amplitude of the alpha rhythm, a shift in the focus of activity from the back of the head and crown, and a weak activation reaction indicate the presence of psychopathology. Beta rhythm
Normally, it is most pronounced in the frontal lobes of the brain and has a symmetrical amplitude (3–5 μV) in both hemispheres. Pathology of the beta rhythm is the following signs:
What do beta rhythm disturbances on the EEG indicate?
The presence of diffuse beta waves with an amplitude no higher than 50-60 μV indicates a concussion. Theta rhythm and delta rhythm
Normally, these slow waves can only be recorded on the electroencephalogram of a sleeping person. In a state of wakefulness, such slow waves appear on the EEG only in the presence of degenerative processes in the tissues of the brain, which are combined with compression, high blood pressure and lethargy. Paroxysmal theta and delta waves in a person in a state of wakefulness are detected when the deep parts of the brain are damaged. 
What do disturbances of theta and delta rhythms on the EEG indicate?
Delta waves with high amplitude indicate the presence of a tumor.Bioelectric activity of the brain (BEA)
This parameter in the EEG conclusion is a complex descriptive characteristic regarding brain rhythms. Normally, the bioelectric activity of the brain should be rhythmic, synchronous, without foci of paroxysms, etc. At the conclusion of the EEG, the doctor usually writes what specific disturbances in the bioelectrical activity of the brain were identified (for example, desynchronized, etc.).
Relatively rhythmic bioelectrical activity with foci of paroxysmal activity in any area of the brain indicates the presence of some area in its tissue where excitation processes exceed inhibition. This type of EEG may indicate the presence of migraines and headaches.Other indicators
Dysfunction of midbrain structures
– this is a mildly expressed disturbance in the activity of brain neurons, which is often found in healthy people, and indicates functional changes after stress, etc. This condition requires only a symptomatic course of therapy.
In general, residual changes in brain structures are the consequences of damage of various types, for example, after injury, hypoxia, viral or bacterial infection. Residual changes are present in all brain tissues and are therefore diffuse. Such changes disrupt the normal passage of nerve impulses.
Changes progress as the volume of education increases. 
Significant slowing of alpha rhythm
may accompany parkinsonism. Fixation of theta and delta waves in the frontal and anterior temporal parts of the brain, which have different rhythms, low frequencies and high amplitudes, is possible in Alzheimer's disease
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