The implication of functional connectivity strength in predicting treatment response of major depressive disorder: A resting EEG study

Tien Wen Lee, Yu Te Wu, Younger W.Y. Yu, Ming Chao Chen, Tai Jui Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

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-min 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.

Original languageEnglish
Pages (from-to)372-377
Number of pages6
JournalPsychiatry Research - Neuroimaging
Volume194
Issue number3
DOIs
StatePublished - 30 Dec 2011

Keywords

  • Coherence
  • Electroencephalography (EEG)
  • Major depression
  • Resting EEG
  • Spectrum

Fingerprint

Dive into the research topics of 'The implication of functional connectivity strength in predicting treatment response of major depressive disorder: A resting EEG study'. Together they form a unique fingerprint.

Cite this