Literature DB >> 17890151

Detrended fluctuation analysis of resting EEG in depressed outpatients and healthy controls.

Jun-Seok Lee1, Byung-Hwan Yang, Jang-Han Lee, Jun-Ho Choi, Ihn-Geun Choi, Sae-Byul Kim.   

Abstract

OBJECTIVE: Recent findings have demonstrated that the EEG possesses long-range temporal (auto-) correlations (LRTC) in the dynamics of broad band oscillations. The analysis of LRTC provides a quantitative index of statistical dependencies in oscillations on different time scales. We analyzed LRTC in resting EEG signals in depressed outpatients and healthy controls.
METHODS: The participants in this study were 11 non-depressed, age-matched controls, and 11 unmedicated unipolar depressed patients. EEG data were obtained from each participant during 5-min resting baseline periods with eyes closed and then analyzed with detrended fluctuation analysis (DFA), a scaling analysis method that quantifies a simple parameter to represent the correlation properties of a time series. The scaling exponent, the result of DFA, provides a quantitative measure of LRTC from the EEG.
RESULTS: The present study demonstrates that all the scaling exponents in depressed patients and healthy controls were greater than 0.5 and less than 1.0, regardless of condition. Furthermore, the scaling exponents of depressed patients have relatively higher values in whole brain regions compared to healthy controls, with significant differences at F3, C3, T3, T4 and O1 channels (p<0.05). Finally, a significant linear correlation was observed between the severity of depression and the scaling exponent over most of the channels, except O2.
CONCLUSIONS: These results suggest that the brain affected by a major depressive disorder shows slower decay of the LRTC, and that the persistence of the LRTC of EEG in depressed patients was associated with the severity of depression over most of the cortical areas. SIGNIFICANCE: The DFA method may broaden our understanding of the psychophysiological basis of depression.

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Year:  2007        PMID: 17890151     DOI: 10.1016/j.clinph.2007.08.001

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  17 in total

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Journal:  J Clin Monit Comput       Date:  2015-02-08       Impact factor: 2.502

2.  A machine learning framework involving EEG-based functional connectivity to diagnose major depressive disorder (MDD).

Authors:  Wajid Mumtaz; Syed Saad Azhar Ali; Mohd Azhar Mohd Yasin; Aamir Saeed Malik
Journal:  Med Biol Eng Comput       Date:  2017-07-13       Impact factor: 2.602

3.  Long-range temporal correlations of broadband EEG oscillations for depressed subjects following different hemispheric cerebral infarction.

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Journal:  Cogn Neurodyn       Date:  2017-08-21       Impact factor: 5.082

4.  Long range temporal correlations in EEG oscillations of subclinically depressed individuals: their association with brooding and suppression.

Authors:  Xavier Bornas; Aina Fiol-Veny; Maria Balle; Alfonso Morillas-Romero; Miquel Tortella-Feliu
Journal:  Cogn Neurodyn       Date:  2014-10-12       Impact factor: 5.082

5.  Resting-state EEG delta power is associated with psychological pain in adults with a history of depression.

Authors:  Esther L Meerwijk; Judith M Ford; Sandra J Weiss
Journal:  Biol Psychol       Date:  2015-01-17       Impact factor: 3.251

6.  The role of comorbid depressive symptoms on long-range temporal correlations in resting EEG in adults with ADHD.

Authors:  Matti Gärtner; Maria Strauß; Jue Huang; Eike Ahlers; Holger Bogatsch; Pierre Böhme; Thomas Ethofer; Andreas J Fallgatter; Jürgen Gallinat; Ulrich Hegerl; Isabella Heuser; Knut Hoffmann; Sarah Kittel-Schneider; Andreas Reif; Daniel Schöttle; Stefan Unterecker
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2022-07-04       Impact factor: 5.270

7.  Combined nonlinear metrics to evaluate spontaneous EEG recordings from chronic spinal cord injury in a rat model: a pilot study.

Authors:  Jiangbo Pu; Hanhui Xu; Yazhou Wang; Hongyan Cui; Yong Hu
Journal:  Cogn Neurodyn       Date:  2016-07-01       Impact factor: 5.082

8.  Medium- and long-term functional behavior evaluations in an experimental focal ischemic stroke mouse model.

Authors:  Juçara Loli de Oliveira; Marina Ávila; Thiago Cesar Martins; Marcio Alvarez-Silva; Elisa Cristiana Winkelmann-Duarte; Afonso Shiguemi Inoue Salgado; Francisco José Cidral-Filho; William R Reed; Daniel F Martins
Journal:  Cogn Neurodyn       Date:  2020-03-19       Impact factor: 5.082

Review 9.  Traumatic brain injury detection using electrophysiological methods.

Authors:  Paul E Rapp; David O Keyser; Alfonso Albano; Rene Hernandez; Douglas B Gibson; Robert A Zambon; W David Hairston; John D Hughes; Andrew Krystal; Andrew S Nichols
Journal:  Front Hum Neurosci       Date:  2015-02-04       Impact factor: 3.169

10.  Comparative study of nonlinear properties of EEG signals of normal persons and epileptic patients.

Authors:  Md Nurujjaman; Ramesh Narayanan; An Sekar Iyengar
Journal:  Nonlinear Biomed Phys       Date:  2009-07-20
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