Nonlinear analysis of EEG complexity in episode and remission phase of recurrent depression

Milena Čukić, Miodrag Stokić, Slavoljub Radenković, Miloš Ljubisavljević, Slobodan Simić, Danka Savić

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)

Abstract

Objectives: Biomarkers of major depressive disorder (MDD), its phases and forms have long been sought. Objectives were to examine whether the complexity of EEG activity, measured by Higuchi's fractal dimension (HFD) and sample entropy (SampEn), differs between healthy subjects, patients in remission, and in episode phase of the recurrent depression and whether the changes are differentially distributed between hemispheres and cortical regions. Methods: Resting state EEG with eyes closed was recorded from 22 patients suffering from recurrent depression (11 in remission, 11 in the episode), and 20 age and sex-matched healthy control subjects. Artifact-free EEG epochs were analyzed by in-house developed programs running HFD and SampEn algorithms. Results: Depressed patients had higher HFD and SampEn complexity compared to healthy subjects. The complexity was higher in patients who were in remission than in those in the acute episode. Altered complexity was present in the frontal and centro-parietal regions when compared to control group. The complexity in frontal and parietal regions differed between the two phases of depressive disorder. Conclusions: Complexity measures of EEG distinguish between the healthy controls, patients in remission and episode. Further studies are needed to establish whether these measures carry a potential to aid clinically relevant decisions about depression.

Original languageEnglish
Article numbere1816
JournalInternational Journal of Methods in Psychiatric Research
Volume29
Issue number2
DOIs
Publication statusPublished - Jun 1 2020

Keywords

  • Higuchi's fractal dimension
  • complexity
  • electroencephalogram
  • recurrent depression
  • sample entropy

ASJC Scopus subject areas

  • Psychiatry and Mental health

Fingerprint

Dive into the research topics of 'Nonlinear analysis of EEG complexity in episode and remission phase of recurrent depression'. Together they form a unique fingerprint.

Cite this