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Changes in the EEG-Rhythms in Endogenous Depressive Disorders and the Effect of Pharmacotherapy

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Abstract

The study of a series of EEG indices in endogenous depressive disorders and their changes after pharmacotherapy was conducted. The EEG changes in depressed patients versus healthy individuals were found to be characterized by a significant increase in the relative power of the Δ- and θ-activity and a decrease in the α- and β-activity, as well as by a decrease in the regional differences between the anterior and posterior divisions of the brain and an increase in the activity of the right hemisphere in relation to the left hemisphere. The use of amitriptyline, fluoxetine, and moclobemide contributed to the improvement in the mental state, which was accompanied by an increase in the EEG amplitude, a decrease in the relative power of the Δ- and θ-activity, and an increase in the α-rhythm power; however, on discharge, the patients retained deviations from a number of values compared to healthy subjects.

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REFERENCE

  1. Sidorenko, G.V., Electroencephalographic Markers and Computer-Based Assessment of the Severity of Depressions, Zh. Nevropatol. Psikhiatr., 1995, vol. 95, no. 1, p. 75.

    Google Scholar 

  2. Zenkov, L.R., Klinicheskaya elektroentsefalografiya (s elementami epileptologii) (Clinical Electroencephalography (with Epileptology Elements)), Taganrog: Izd. TRTU, 1996, p. 358.

    Google Scholar 

  3. Mel'nikova, T.S., Nikiforova, A.I., Koptelov, Yu.M., et al., Interhemispheric Correlation of the Brain Electrical Activity in Late-Onset Depressions, Zh. Nevropatol. Psikhiatr., 1992, vol. 92, no. 1, p. 88.

    Google Scholar 

  4. Strelets, V.B., Inter-and Intrahemispheric Disorders in Certain Types of Cerebral Pathology, Zh. Vyssh. Nervn. Deyatel., 1993, vol. 43, no. 2, p. 262.

    Google Scholar 

  5. Strelets, V.B., Ivanitskii, A.M., and Artseulova, O.K., Dynamics of Neurophysiological Parameters in Reactive (Situational) and Endogenous Depression, Fiziol. Chel., 1994, vol. 20, no. 6, p. 64.

    Google Scholar 

  6. Ohashi, Y., The Baseline EEG Traits and the Induced EEG Changes by Chronic Antidepressant Medication in Patients with Major Depression. Early Prediction of Clinical Outcomes Solely Based on Quantification and Mapping of EEG, Psychiatr. Neurol. Jpn., 1994, vol. 96, no. 6, p. 444.

    Google Scholar 

  7. Bruder, G.E., Fong, R., Tenke, C.E., et al., Regional Brain Asymmetries in Major Depression with or without an Anxiety Disorder: A Quantitative Electroencephalographic Study, Biol. Psychiatr., 1997, vol. 41, no. 9, p. 939.

    Google Scholar 

  8. Mas, F., Prichep, L.S., and Alper, K., Treatment-Resistant Depression in a Case of Minor Head Injury: An Electrophysiological Hypothesis, Clin. Electroencephalogr., 1993, vol. 24, no. 3, p. 118.

    Google Scholar 

  9. Knott, V.J., Telner, J.I., Lapierre, Y.D., et al., Quantitative EEG in the Prediction of Antidepressant Response to Imipramine, J. Affective Disorders, 1996, vol. 39, no. 3, p. 175.

    Google Scholar 

  10. Omel'chenko, V.P., Computer-Based Analysis of the Brain Biopotentials as the Basis of the Assessment and Pharmacological Correction of Psychopathological States, Doctoral (Biol.) Dissertation, Rostov-on-Don, 1990.

  11. Aivazyan, S.A., Enyukov, I.S., and Meshalkin, L.D., Prikladnaya statistika: osnovy modelirovaniya i pervichnaya obrabotka dannykh (Applied Statistics: The Basis for Modeling and Primary Data Processing), Moscow: Finansy i Statistika, 1983, p. 471.

    Google Scholar 

  12. Mel'nikova, T.S. and Nikiforova, A.I., Neurophysiolgy of Deep Divisions of the Brain in Late-Onset Depressions: Its Peculiarities and the Influence of Course Therapy, Vestn. Ross. Akad. Med. Nauk, 1992, no. 8, p. 21.

  13. Kulaichev, A.P., Komp'yuternaya elektrofiziologiya v klinicheskoi i issledovatel'skoi praktike. CONANm, – 3.0 dlya Windows (Computer-Based Electrophysiology in Clinical Practice and Research. CONANm,—3.0 for the Windows), Moscow: Informatsiya i Komp'yutery, 1998, p. 284.

    Google Scholar 

  14. Wheeler, R.E., Davidson, R.Y., and Tomarkin, A.I., Frontal Brain Asymmetry and Emotional Reactivity: A Biological Substrate of Affective Style, Psychophysiol. J. Res., 1991, vol. 30, no. 1, p. 82.

    Google Scholar 

  15. Swartzburg, M., Hemispheric Laterality and EEG Correlates of Depression, Res. Commun. Psychiatr. Behav., 1983, vol. 8, no. 2, p. 187.

    Google Scholar 

  16. Monakhov, K.K., Panyushkina, S.V., Bochkarev, V.K., and Nikiforov, A.I., Neurophysiological Programs of the Cerebral Activity and the Peculiarities of Their Structure in Different Psychopathological States and in the Process of Treatment, Fiziol. Zh. SSSR, 1984, vol. 70, no. 7, p. 1023.

    Google Scholar 

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Omel'chenko, V.P., Zaika, V.G. Changes in the EEG-Rhythms in Endogenous Depressive Disorders and the Effect of Pharmacotherapy. Human Physiology 28, 275–281 (2002). https://doi.org/10.1023/A:1015596416791

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  • DOI: https://doi.org/10.1023/A:1015596416791

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