Electroencephalography entropy and depression

Kanunikov I.E.; Kleeva D.F.

doi:https://doi.org/10.17116/jnevro2022122071106

Kanunikov I.E.

Center for Bioelectric Interfaces of the Saint Petersburg State University

Kleeva D.F.

National Research University Higher School of Economics

Electroencephalography entropy and depression

Authors:

Kanunikov I.E., Kleeva D.F.

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Journal: S.S. Korsakov Journal of Neurology and Psychiatry. 2022;122(7): 106‑110

DOI: 10.17116/jnevro2022122071106

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To cite this article:

Kanunikov IE, Kleeva DF. Electroencephalography entropy and depression. S.S. Korsakov Journal of Neurology and Psychiatry. 2022;122(7):106‑110. (In Russ.)
https://doi.org/10.17116/jnevro2022122071106

Подписка 2026 Журнал неврологии и психиатрии им. С.С. Корсакова (S.S. Korsakov Journal of Neurology and Psychiatry)

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OBJECTIVE

The study is devoted to finding the relationship between EEG entropy indices and depression, assessed using the Beck Depression Inventory.

MATERIAL AND METHODS

The experiments involved 42 people aged 20—25 years. Each of them completed the psychological tests of Beck (depression), Spielberger (anxiety), and Wasserman (frustration). Background EEG recording with eyes open and closed was carried out in the following 14 leads: F3, F4, F7, F8, T3, T4, T5, T6, C3, C4, P3, P4, O1, O2. The following 4 EEG entropy indices were calculated: Shannon’s entropy, sample entropy, permutation and recurrent entropy. To calculate the multiple correlation of the EEG entropy with the indicators of psychological tests, a factor analysis of the EEG entropy indicators was carried out using the principal component method. As a result, the correlation of the main component with psychological tests was calculated.

RESULTS

Significant (p<0.05; p<0.01) negative relationships were found for all types of EEG entropy with the Beck index scale reflecting the somatic manifestations of depression (Beck2) and with the normalized index characterizing the Beck2/Beck ratio. No significant correlations of EEG entropy with the Spilberger and Wasserman test scores were found, suggesting that depression and anxiety are based on different brain mechanisms.

CONCLUSION

The fact that there is a negative correlation between the EEG entropy and the scale reflecting the somatic manifestations of depression indicates that people with a more complex and less predictable EEG are better able to resist the somatic manifestations of depression. In other words, the high information capacity of the system allows it to respond flexibly to rapidly changing and unpredictable circumstances.

Keywords:

depression

EEG entropy

Beck Depression Inventory

Authors:

Kanunikov I.E.

Center for Bioelectric Interfaces of the Saint Petersburg State University

Kleeva D.F.

National Research University Higher School of Economics

Received:

21.01.2022

Accepted:

24.02.2022

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References:

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