期刊
PSYCHIATRY RESEARCH-NEUROIMAGING
卷 194, 期 3, 页码 372-377出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.pscychresns.2011.02.009
关键词
Major depression; Electroencephalography (EEG); Resting EEG; Coherence; Spectrum
资金
- National Science Council, Taiwan, ROC [NSC 90-2314-B-075-068]
- Kai-Suan Psychiatric Hospital-Kaohsiung, Taiwan, ROC [KS92-015]
Predicting treatment response in major depressive disorder (MDD) has been an important clinical issue given that the initial intent-to-treat response rate is only 50 to 60%. This study was designed to examine whether functional connectivity strengths of resting EEG could be potential biomarkers in predicting treatment response at 8 weeks of treatment. Resting state 3-mM eyes-closed EEG activity was recorded at baseline and compared in 108 depressed patients. All patients were being treated with selective serotonin-reuptake inhibitors. Baseline coherence and power series correlation were compared between responders and non-responders evaluated at the 8th week by Hamilton Depression Rating Scale. Pearson correlation and receiver operating characteristic (ROC) analyses were applied to evaluate the performance of connectivity strengths in predicting/classifying treatment responses. The connectivity strengths of right fronto-temporal network at delta/theta frequencies differentiated responders and non-responders at the 8th week of treatment, such that the stronger the connectivity strengths, the poorer the treatment response. ROC analyses supported the value of these measures in classifying responders/non-responders. Our results suggest that fronto-temporal connectivity strengths could be potential biomarkers to differentiate responders and slow responders or non-responders in MDD. (C) 2011 Elsevier Ireland Ltd. All rights reserved.
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