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Human Physiology

, Volume 44, Issue 6, pp 627–634 | Cite as

Features of EEG Spectral Parameters in Depressive Patients with Different Efficiencies of Decision-making

  • A. F. Iznak
  • E. V. Iznak
  • T. I. Medvedeva
  • I. V. Oleichik
  • E. R. Nikolaeva
Article
  • 4 Downloads

Abstract

We analyzed the relationships between the EEG spectral parameters in depressed patients reflecting the functional state of the brain, and the efficiency of their decision-making based on both logic and emotional learning in order to clarify the neurophysiological mechanisms underlying decision-making impairments. As a result of multivariate cluster analysis based on 96 EEG spectral power parameters, two subgroups of depressive patients were identified. The groups differ in the EEG amplitude-frequency and spatial characteristics, but do not differ either in age or in severity of depression. The subgroup of depressive patients who formed cluster 2 and had higher spectral powers of the EEG ∆ (2–4 Hz), θ1 (4–6 Hz), θ2 (6–8 Hz), α1 (8–9 Hz) and α2 (9–11 Hz) subbands, as compared with the patients who formed cluster 1, had a higher level of cognitive test performance that requires decision-making: the Wisconsin Card Sorting Test (WCST), which evaluates logic-based decision-making, and the Iowa Gambling Task (IGT), which evaluates decision-making based on emotional learning. Cluster 2 patients also exhibited a better long-term memorization (in the ten-word long-term memory test) compared with those who formed cluster 1. Judging by the EEG parameters, the neurophysiological mechanisms of inhibition are more intact in patients forming cluster 2 than in cluster 1 patients who have lower spectral power values of the EEG ∆ (2–4 Hz), θ1 (4–6 Hz), θ2 (6–8 Hz), α1 (8–9 Hz), and α2 (9–11 Hz) subbands. The impairment of decision-making functions in depressive patients may, at least partially, be due to the deficit of the brain inhibition mechanisms that ensure normal integrative brain activity, including such higher mental functions as memory, attention, and decision-making.

Keywords:

depression decision-making quantitative EEG 

Notes

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Copyright information

© Pleiades Publishing, Inc. 2018

Authors and Affiliations

  • A. F. Iznak
    • 1
  • E. V. Iznak
    • 1
  • T. I. Medvedeva
    • 1
  • I. V. Oleichik
    • 1
  • E. R. Nikolaeva
    • 1
  1. 1.Mental Health Research Centre,MoscowRussia

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