Functional connectivity abnormalities during processing of predictive stimuli in patients with major depressive disorder

Noa Fogelson, Pablo Diaz-Brage, Ling Li, Avi Peled, Ehud Klein

Research output: Contribution to journalArticlepeer-review

Abstract

The study investigated the underlying mechanisms associated with the ability of patients with major depressive disorder (MDD) to utilize predictive contextual information in order to facilitate detection of predictable versus random targets. To this end we evaluated EEG event-related functional connectivity during the processing of predictive stimuli in MDD and control subjects. A target detection task was used where targets were either preceded by randomized sequences of standards, or by sequences that included a predictive sequence. Functional connectivity was evaluated using synchronization likelihood and graph theory. The cluster coefficient and local efficiency values were greater in MDD compared to controls, during the processing of the three stimuli consisting of the predictive sequence, in the beta frequency band, suggesting an increased structured network organization. These changes were associated with increased functional connectivity within frontal networks in MDD patients compared to controls. However, no significant functional connectivity group-changes were observed for target conditions or randomized standards. These findings suggest that MDD is associated with context-specific functional connectivity abnormalities during the processing of predictive stimuli.

Original languageEnglish
Article number146543
JournalBrain Research
Volume1727
DOIs
StatePublished - 15 Jan 2020
Externally publishedYes

Keywords

  • EEG
  • Functional connectivity
  • Graph theory
  • Major depression
  • Prediction

Fingerprint

Dive into the research topics of 'Functional connectivity abnormalities during processing of predictive stimuli in patients with major depressive disorder'. Together they form a unique fingerprint.

Cite this