Spectral power of the beta rhythm of the electroencephalogram as a marker of depressive disorder

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Abstract

The aim of this study was to identify the features of electroencephalograms in patients with depressive disorders and to evaluate correlations with clinical and dynamic parameters.

Material and methods. The study included 74 patients with depressive disorder. The severity of depressive disorder was assessed using the Hamilton depression scale and the General clinical impression scale. To assess the clinical features of the course of depressive disorder, the Hamilton anxiety scale, the Snaith–Hamilton anhedonia scale, and the social adaptation scale were used. Information about the age of depressive disorder was taken from patients’ medical records. In addition to the clinical data, the level of cognitive flexibility was assessed using the Stroop test. The electroencephalogram was recorded and analyzed using the international 10–20 system at rest with closed eyes. The values of the spectral power of rhythms were analyzed. Correlation analysis of clinical and electroencephalographic data of patients was performed.

Results. Analysis of the spectral power of rhythms revealed statistically significant differences between the group of patients with depressive disorders and the control only in the β-frequency range in the frontal (p=0.000001), central (p=0.00028) and parietal (p=0.017) cortex. Direct correlations were found between the level of beta — rhythm spectral power in the frontal cortex and the severity of depressive disorder (r=0.2856; p=0.015), the level of anxiety (r=0.2622; p=0.028), and the degree of cognitive rigidity (r=0.3728; p=0.007). Direct correlations were also found between the spectral power of the β-rhythm in the central cortex and the degree of cognitive rigidity (r=0.3332; p=0.017).

Conclusions. The predominance of high-frequency activity in patients with depressive disorders reflects an increase in cortical arousal in the brain, which is accompanied by a number of clinical features in the form of a more severe course of the disease, the presence of anxiety symptoms and cognitive rigidity. Thus, the results obtained allow us to use quantitative electroencephalogram data to clarify the severity of clinical symptoms of depressive disorder.

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About the authors

Stanislav A. Galkin

Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences

Author for correspondence.
Email: s01091994@yandex.ru
Russian Federation, 634014, Tomsk, Aleutskaya str., 4

Svetlana N. Vasilyeva

Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences

Email: vasilievasn@yandex.ru
Russian Federation, 634014, Tomsk, Aleutskaya str., 4

German G. Simutkin

Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences

Email: ggsimutkin@gmail.com
Russian Federation, 634014, Tomsk, Aleutskaya str., 4

Svetlana A. Ivanova

Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences; Siberian State Medical University

Email: ivanovaniipz@gmail.com
Russian Federation, 634014, Tomsk, Aleutskaya str., 4; 634050, Tomsk, Moscow trakt, 2

Nikolaj A. Bokhan

Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences; Siberian State Medical University

Email: mental@tnimc.ru
Russian Federation, 634014, Tomsk, Aleutskaya str., 4; 634050, Tomsk, Moscow trakt, 2

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Supplementary files

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1. Fig. 1. Stroop test data

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2. Fig. 2. Spectral power of electroencephalography; Me [Q1; Q3]; p is the level of statistical significance when comparing groups using the Mann-Whitney U-test

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Copyright (c) 2021 Galkin S.A., Vasilyeva S.N., Simutkin G.G., Ivanova S.A., Bokhan N.A.

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