EEG alpha band characteristics in patients with a depressive episode within recurrent and bipolar depression

Autor: Nikolay A. Bokhan, Stanislav A. Galkin, Svetlana N. Vasilyeva
Jazyk: English<br />Russian
Rok vydání: 2023
Předmět:
Zdroj: Consortium Psychiatricum, Vol 4, Iss 3, Pp 5-12 (2023)
Druh dokumentu: article
ISSN: 2712-7672
2713-2919
DOI: 10.17816/CP6140
Popis: BACKGROUND: The search for biological markers for the differential diagnosis of recurrent depression and bipolar depression is an important undertaking in modern psychiatry. Electroencephalography (EEG) is one of the promising tools in addressing this challenge. AIM: To identify differences in the quantitative characteristics of the electroencephalographic alpha band activity in patients with a depressive episode within the framework of recurrent depression and bipolar depression. METHODS: Two groups of patients (all women) were formed: one consisting of subjects with recurrent depressive disorder and one with subjects experiencing a current mild/moderate episode (30 patients), and subjects with bipolar affective disorder or a current episode of mild or moderate depression (30 patients). The groups did not receive pharmacotherapy and did not differ in their socio-demographic parameters or total score on the Hamilton depression scale. A baseline electroencephalogram was recorded, and the quantitative characteristics of the alpha band activity were analyzed, including the absolute spectral power, interhemispheric coherence, and EEG activation. RESULTS: The patients with recurrent depressive disorder demonstrated statistically significantly lower values of the average absolute spectral power of the alpha band (z=2.481; p=0.042), as well as less alpha attenuation from eyes closed to eyes open (z=2.573; p=0.035), as compared with the patients with bipolar affective disorder. CONCLUSION: The presented quantitative characteristics of alpha activity are confirmation that patients with affective disorders of different origins also display distinctive electrophysiological features which can become promising biomarkers and could help separate bipolar depression from the recurrent type.
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