RU2706666C1 - Diagnostic technique for functional state of brain by neural networks synchronization parameters - Google Patents

Abstract

FIELD: psychophysiology.

SUBSTANCE: invention refers to medicine, namely to psychophysiology, and can be used for diagnosing the functional state of the brains of subjects aged 20–60 years at different health levels. That is ensured by diagnosing the functional state of the brain by neural network synchronization parameters. Brain biopotentials in a state of rest with open and closed eyes are recorded. Cerebral biopotentials are recorded in cognitive tasks recorded within 15–30 minutes. Analysis epochs are detected in 2.5 seconds without artefacts. That is followed by detection of generalizations – sections of treated encephalograms, where more than 80 % of leads have single frequency of biopotentials, i.e. synchronized. Tables are formed with presence of interhemispheric asymmetry of more than 15 % of alpha-rhythm spectrum power. Graphs of interhemispheric and intrahemispheric asymmetry are plotted on detected periodically occurring sections of synchronization. Expression in % of intra- and interhemispheric asymmetry of synchronization processes is determined. Obtained variations of cortical synchronization asymmetry (by frequency, period and manifestation of asymmetry) enable to diagnose functional state and formed disorders in interaction of cortical and subcortical structures in a specific individual.

EFFECT: method provides accurate diagnosis of the functional state of the brain by evaluating neuron network synchronization parameters in various functional samples based on the selection of variations of intra- and interhemispheric asymmetry of a pattern of bark cortex synchronization.

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Description

The invention relates to medicine, in particular to the field of psychophysiology, and can be used to diagnose the functional state of the brain of patients aged 20-60 years at various levels of health.

The functional state of the body in the interval between norm and pathology determines the risk of the onset and development of the disease. In recent decades, ideas about a gradual change in a person’s health status, about the quality and quantity of his health have become increasingly used. This approach to assessing health corresponds to the accepted classification of body conditions, which includes:

- conditions with sufficient functional (adaptive) reserve;

- prenosological conditions in which adverse changes in the body's work are compensated by a higher than normal tension of regulatory systems;

- premorbid conditions characterized by a decrease in the functional reserves of the body;

- the state of failure of adaptation, decompensation, and the development of diseases (Kaznacheev V.P., Baevsky P.M., Berseneva A.P. Donosological diagnostics in the practice of mass screening of the population. - L. - 1980. P. 99-131).

The timely detected state of “tension” of regulatory systems allows you to recognize the causes of dysfunctions, create conditions for the body to compensate for the effects of traumatic effects, increase reserve capabilities. The degree of synchronization of neural networks is associated with the processes of neuroplasticity and partly reflects the adaptive potential of the nervous system.

The essence of any adaptable system is the ability to adjust its reactions according to changes in the stimulus based on existing experience, as well as to accumulate and store new information. That is why adaptation is possible only on condition that the memory mechanisms are preserved and work clearly. The central nervous system (CNS) is the main link in the chain of formation of general non-specific adaptive reactions, each of which corresponds to its own level of functional activity of the body. The formation of intercentral connections of the cerebral cortex with subcortical structures creates a stable morphological and functional basis for optimizing the adaptive reactions of the body, thus indicating the relationship between the functional state of the brain and the type of adaptive reaction [Korobeinikova EP Changes in the alpha rhythm of a person during general non-specific adaptive reactions caused by an alternating magnetic field. // The use of lasers and magnets in biology and medicine. - Rostov-n / D., 1983. - S. 64-65].

According to [S.I. Aksenov, Water and its role in the regulation of biological processes. Moscow-Izhevsk, Institute for Computer Research. 2004. S. 24-28] the constant movement from one unstable state to another allows living organisms to adequately adapt to continuously changing external conditions. Thus, in living organisms, their own biorhythms were synchronized with the external rhythms of the living environment [Breus TK, Rappoport S.I. // Magnetic storms: biomedical and geophysical aspects. M: Soviet sports. 2003.192 p.].

The main regulator of biorhythms and the vital processes caused by them is the brain [Zhuravlev, B.V. Reverb cyclicity between nerve cells of the brain as a mechanism of self-regulatory systems of the body / B.V. Zhuravlev - M .: GU Research Institute of Normal Physiology. PC. Anokhina RAMS, - 2006, - 194 p.]. The biorhythm of the brain is associated with individual characteristics of the mechanisms of self-regulation and the level of plasticity of neurodynamic processes [Soroko, S.P. Features aimed reorganizations EEG parameters in humans using the method of adaptive biocontrol / S.P. Soroko, T.J. Musuraliev // Human Physiology. - 1995. - T. 21, No. 5. - P. 5-8]. It was shown that the level of self-regulation is higher in those individuals whose periodic components are expressed in electroencephalograms (EEGs) that have stable connections of individual rhythms with alpha rhythm in the EEG time structure.

Significant attention is paid to the study of the synchronization of various parts of the cerebral cortex of alpha and beta rhythms in the processes of regulation and changes in the functional state of the body [Ivanitsky A.M., Nikolaev A.R., Ivanitsky G.A. Cortical connectivity during word association search // Int. J. Psychophysiol. - 2001. Vol. 42. No 1. - pp. 35-53; Nunez P., Wingeier B., Silberstein R. Spatial-temporal structures of human alpha rhythms: theory, microcurrent sources, multiscale measurements, and global binding of networks // Hum. Brain Mapp. - 2001. V. 13. - pp. 125-164; Soroko S.I. Aldasheva A.A. Individual strategies of human adaptation to extreme conditions // Human Physiology. - 2012. - T. 38. - No. 6. - P. 78-86].

For an objective characterization of a person’s functional state in norm and pathology, indicators of brain bioelectric activity are widely used. Its most studied form is the electroencephalogram (EEG). Many methods have been developed for analyzing brain biorhythms recorded using EEG [Rusinov B.C., Grindel OM, Boldyreva GN, Vakar EM Biopotentials of the human brain (mathematical analysis). - M .: Medicine, 1987. S. 67-254].

A known method of detecting a shift in the level of constant electric potential of the brain when assessing the stability of a functional state (see patent RU No. 2007116, IPC AB 5/04, publication date 02/15/1994), in which a pair of recording electrodes are mounted on the subject’s head over a given area of the brain, the electrodes are connected to an electric voltage amplifier, the output of which is read at the beginning and at the end of the shear caused by external influence, the values of the constant electric potential and compare them with each other.

The disadvantages of this method are the increased complexity of the registration process and the limited scope, the lack of differential diagnosis of activated brain regions, as well as low information content and low accuracy of the results due to the instability of the electrode resistance.

A known method for diagnosing the degree of psychophysiological maladaptation (RF patent No. 2154979, IPC АВВ 5/0476, publication date 02/10/2000), including recording the brain’s biopotentials at rest, followed by a quantitative analysis of the frequency-amplitude characteristics of the electroencephalogram, in particular in the alpha- activity with an estimate of the spectral power of alpha activity at the absolute power of alpha activity of less than 10 microvolts ² or absolute power values of alpha activity greater than 80 microvolts ² and / or alpha relative power aktivnos and more than 50% diagnosed with a significant degree of psychophysiological maladjustment.

However, the alpha rhythm analyzed in the method is the dominant rhythm of passive wakefulness at rest with closed eyes, recorded in the caudal regions of the brain, in the projection of the visual cortex, which cannot objectively reflect the functional adaptation and maladaptation of the brain, without analyzing the spectral-frequency characteristics of synchronization of different There are no objective criteria analyzing adaptation processes and the nature of functional activity without brain structures without a mental load test.

The technical task of the invention is the development of a method for diagnosing the functional state of the brain by the synchronization parameters of neural networks in various functional tests.

The technical result achieved in solving the problem is expressed in identifying, analyzing the parameters of the periodic synchronization of the cortical departments among themselves, obtaining for the first time on their basis a set of models (variations) of inter- and intrahemispheric asymmetry of the synchronization picture of the cortical departments.

The obtained variations in the asymmetry of synchronization of the cortical departments (in frequency, period, and severity of asymmetry) will allow us to diagnose the functional state and emerging disorders in the interaction of cortical and subcortical structures in a particular individual.

The technical problem is solved by a method for diagnosing the functional state of the brain according to the parameters of synchronization of neural networks, based on the registration of brain biopotentials at rest with open and closed eyes, registration of brain biopotentials when solving a cognitive task, recorded within 15-30 minutes, from recorded EEGs distinguish epochs of analysis in 2.5 seconds without artifacts, where more than 40% of the leads are synchronized at one frequency in the region of 7-13 Hz; carry out periodometric analysis of all selected eras in the alpha range of 7-13 Hz; further, the generalizations are identified - areas of processed encephalograms, where more than 80% of the leads have a single frequency of biopotentials., i.e. synchronized; form tables with more than 15% interhemispheric asymmetry by the power of the alpha rhythm spectrum; build graphs of interhemispheric and intrahemispheric asymmetry on identified periodically occurring synchronization sections; determine the severity in% of the intra and hemispheric asymmetry of the synchronization processes.

The essence of the method for analyzing synchronization between the interhemispheric and intrahemispheric sections of the cerebral cortex (hereinafter referred to as the synchronization analysis) ”is that not only the amplitude-frequency characteristics of the brain biocurrents are analyzed in different samples, but the general pattern of periodically repeating synchronization between a certain set of sections of the cerebral cortex is revealed.

Periodic synchronization processes between the lead network (from different parts of the cortex) reflect the flexibility of the nervous system in adjusting to emerging external rhythms, and the ability to quickly adjust the state under "disturbances" of the external environment. In studies of the regulatory processes of the body with changes in the geomagnetic environment, it was shown that the reaction to single magnetic storms has a 3-phase form (synchronization, desynchronosis and relaxation phase); at the same time, for healthy people, the predominance of the phase of synchronization is characteristic, for patients - desynchronosis. [Chibisov S.M. RUDN University Bulletin, a series of "Medicine", 2006. No. 3. S. 35-44; Ragulskaya M.V., Chibisov S.M. The successes of modern science. 2008. No2. S.14-19.].

et al. NeuroImage. 2004. V. 22. N.3. P. 1023-1028; Klimesch et al. Brain Res. Rev. - 2007. V. 53. - pp. 63-88]. Возможно, благодаря такому «функциональному ядру» и обнаруживаются регулярные паттерны синхронизации именно в альфа-диапазоне.Well-pronounced synchronization of the cortical regions on the EEG is observed in the alpha range. Studies show that the "functional core" that organizes the bioelectric activity of the brain in other frequency ranges is formed by oscillations at the frequency of alpha activity [

et al. NeuroImage 2004. V. 22. N.3. P. 1023-1028; Klimesch et al. Brain Res. Rev. - 2007. V. 53. - pp. 63-88]. Perhaps, thanks to this “functional core”, regular synchronization patterns are found precisely in the alpha range.

The invention is illustrated graphic materials: Fig. 1 shows a type of synchronization of a neural network, on which a record of a type of synchronization of dominant neural networks is presented; FIG. 2 - an example of the allocation of EEG eras for analysis.

The algorithm for identifying and analyzing the synchronization of neural networks consists of the following steps:

At the preparatory stage, it is necessary to use an encephalograph with at least 16 electrodes. For analysis, you will need EEG recordings from 15 to 30 minutes, of which the analysis epochs of 2.5 seconds are distinguished without artifacts, i.e. the entire record is divided into intervals of 2.5 seconds, from which eras (EEG sections) with artifacts are removed (Fig. 2).

After choosing epochs for analysis, a periodometric analysis of all epochs in the alpha range is carried out, i.e. from 7 to 13 Hz. The key indicators that will be needed to identify neural networks in these epochs are: leads, A — spectrum amplitude, μV / s; S is the spectrum power, μV ² / s ² ; F is the frequency, Hz; The rhythm index is%.

After receiving tables with the necessary indicators for each era, step-by-step identification and analysis of the synchronization of neural networks is carried out:

1) Choose the EEG era in 2.5 seconds, in which more than 40% of the leads are synchronized at one frequency in the region from 7 to 13 Hz.

2) Reveal generalization, i.e. eras in which more than 80% of the leads are “synchronized”, i.e. have the same frequency ± 0.1 Hz. Actually, not the leads are synchronized, but the alpha rhythm (Table 1 - periodometric analysis with the detection of synchronization between more than 80% of the leads).

3) In order to identify asymmetries in the activity of hemispheres and areas of increased cortical activity, which may reflect dysfunctions in the functional state and the functioning of neural networks, it is necessary to form tables of interhemispheric asymmetry of more than 15%) for the full power of the alpha rhythm spectrum (S full) (Table 2 - Periodometric analysis in the alpha range. Spectrum and frequencies (Alpha) 0 s, Background recording). For example, researchers attribute the asymmetry in the right prefrontal cortex to impaired emotional response, increased anxiety and sleep disturbance. Table 2 shows that the asymmetry in the frontal and temporal regions is about 50%, which is associated with disturbances in the regulation of the emotional state and depressive states (which is confirmed by the history of this patient). Moreover, the assignment of Fp2A2 (10.8 Hz, instead of 9.7 Hz ± 0.1) is not included in the structure of the active neural network at all.

An example of the identification and analysis of synchronization of neural networks.

1) With a long-term registration of EEG (more than 30 minutes), the subject distinguishes between the epochs of the EEG analysis of 2.5 seconds, the periodometric analysis shows the synchronization sections of different parts of the cortex for each epoch. The criterion for the synchronization pattern is the presence of synchronization at a single alpha rhythm frequency in more than 40% of EEG derivations (Table 3 - Synchronization pattern in the background recording at a frequency of 9.8 Hz. Isp. Grev, 33 years. Spectrum and frequencies (Alpha ) 38 s, era 4.). From Tables 3 and 4 of one subject it is clearly seen that the synchronization pattern between one set of leads is repeated - these are leads F3, F4, C3, C4, P3, P4 and T3, T4. Outwardly, such synchronization in the leads reflects the contour of the neural network, this figure is periodically repeated throughout the entire EEG record for each subject.

2) Erases with synchronization between 80% and a large number of leads can also be distinguished, for example, as in table 1.

3) According to the received individual patterns of synchronization of the neural network in terms of power (severity of rhythm), asymmetry is detected in symmetrical different-hemisphere sections (leads), for example, in the temporal regions as shown in Table 4 - with increased activity (excitability) of the right temporal region associated with increased anxiety .

4) In subsequent similar analyzed eras, the frequency and severity of asymmetry sections are revealed with the identification of the most significant in a particular individual to assess the functional state of a person and the degree of dysfunction. In the given example, the subject had minor deviations from the norm in a functional state with pronounced excitability in the emotional sphere - increased anxiety.

Such an analysis of the functional state of the nervous system through the identification of asymmetries in the work of the neural network allows us to reliably show both the presence of dysfunctions of the synchronization processes between different parts of the cortex and their localization.

The inventive method for determining the functional interhemispheric asymmetry and the degree of synchronization of neural networks allows you to analyze the synchronization between the interhemispheric and intrahemispheric sections of the cerebral cortex during a rest state with open and closed eyes, solving a cognitive task.

This method allows you to evaluate the speed, frequency, frequency and spectral characteristics of the processes of synchronization of neural networks and is an objective and non-invasive method for testing the functions of the central nervous system.

A is the amplitude of the spectrum, μV / s;

S is the spectrum power, μV ² / s ² ;

F is the frequency, Hz;

The rhythm index is%.

A is the amplitude of the spectrum, μV / s;

S is the spectrum power, μV ² / s ² ;

F is the frequency, Hz;

The rhythm index is%.

A is the amplitude of the spectrum, μV / s;

S is the spectrum power, μV ² / s ² ;

F is the frequency, Hz;

The rhythm index is%.

A is the amplitude of the spectrum, μV / s;

S is the spectrum power, μV ² / s ² ;

F is the frequency, Hz;

The rhythm index is%.

List of references:

1. Klimesch W., Sauseng P., Hanslmayr S. EEG alpha oscillation: The inhibition-timing hypothesis // Brain Res. Rev. - 2007. V. 53. - pp. 63-88

E.,

P.A., Miwakeichi T. et al. Concurrent EEG/FMRI analysis by multiway Partial Least Squares // NeuroImage. 2004. V. 22. N.3. P. 1023-1028.2.

E.,

PA, Miwakeichi T. et al. Concurrent EEG / FMRI analysis by multiway Partial Least Squares // NeuroImage. 2004. V. 22. N.3. P. 1023-1028.

3. Ragulskaya, M.V. The main stages of development of ideas about the influence of space on the biosphere and noosphere / M.V. Ragulskaya, S.M. Chibisov / Scientific journal. The successes of modern science. - 2008. - N2. - S. 14-19.

4. Chibisov S.M. Space and biosphere. The influence of magnetic storms on the chronostructure of biological rhythms. // Bulletin of RUDN University, series "Medicine", 2006, No. 3, P. 35-44.

5. Breus TK, Rappoport S.I. // Magnetic storms: biomedical and geophysical aspects. M: Soviet sports. 2003.192 p.

6. Kaznacheev V.P., Baevsky P.M., Berseneva A.P. Pre-nosological diagnostics in the practice of mass population surveys. - L. - 1980.P. 99-131

7. Korobeinikova EP Changes in the alpha rhythm of a person during general non-specific adaptive reactions caused by an alternating magnetic field. // The use of lasers and magnets in biology and medicine. - Rostov-n / D., 1983. - S. 64-65

8. S.I. Aksenov, Water and its role in the regulation of biological processes. Moscow-Izhevsk, Institute for Computer Research. 2004.S. 24-28

9. Zhuravlev, B.V. Reverb cyclicity between nerve cells of the brain as a mechanism of self-regulatory systems of the body / B.V. Zhuravlev - M .: GU Research Institute of Normal Physiology. PC. Anokhina RAMS, - 2006, - 194 p.

10. Soroko, S.P. Features aimed reorganizations EEG parameters in humans using the method of adaptive biocontrol / S.P. Soroko, T.J. Musuraliev // Human Physiology. - 1995. - T. 21, No. 5. - P. 5-8

11. Ivanitsky A.M., Nikolaev A.R., Ivanitsky G.A. Cortical connectivity during word association search // Int. J. Psychophysiol. - 2001. Vol. 42. No 1. - pp. 35-53;

12. Nunez P., Wingeier B., Silberstein R. Spatial-temporal structures of human alpha rhythms: theory, microcurrent sources, multiscale measurements, and global binding of networks // Hum. Brain Mapp. - 2001. V. 13. - pp. 125-164;

13. Soroko S.I. Aldasheva A.A. Individual strategies of human adaptation to extreme conditions // Human Physiology. - 2012. - T. 38. - No. 6. - P. 78-86

14. Rusinov B.C., Grindel O.M., Boldyreva G.N., Vakar E.M. Biopotentials of the human brain (mathematical analysis). - M.: Medicine, 1987.S. 67-254.

Claims (1)

A method for diagnosing the functional state of the brain according to the parameters of synchronization of neural networks, characterized in that, based on recording the brain’s biopotentials at rest with open and closed eyes, registering the brain’s biopotentials when solving a cognitive task, recorded within 15-30 minutes, from recorded EEG is detected by analyzing the era in 2.5 seconds, in which more than 40% of the leads are synchronized at a frequency of 7-13 Hz; carry out periodometric analysis of all selected eras in the alpha range of 7-13 Hz; then they carry out the identification of generalizations - areas of processed encephalograms, where more than 80% of the leads are synchronized; form tables of interhemispheric asymmetry of more than 15% of the total power of the alpha rhythm spectrum, build graphs of interhemispheric and intrahemispheric asymmetry from periodically occurring patterns of synchronization with a degree of similarity of more than 80%, determine the degree of intra- and interhemispheric asymmetry and its localization in a particular individual.

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