Title of article :
Detrended fluctuation analysis of resting EEG in depressed outpatients and healthy controls
Author/Authors :
Jun Seok Lee، نويسنده , , Byung-Hwan Yang، نويسنده , , Jang-Han Lee، نويسنده , , Jun-Ho Choi، نويسنده , , Ihn-Geun Choi، نويسنده , , Sae-Byul Kim، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2007
Pages :
8
From page :
2489
To page :
2496
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.
Keywords :
Major depressive disorder , EEG , Detrended fluctuation analysis
Journal title :
Clinical Neurophysiology
Serial Year :
2007
Journal title :
Clinical Neurophysiology
Record number :
524275
Link To Document :
بازگشت