Classifying different emotional states by means of EEG-based functional connectivity patterns

PLoS One. 2014 Apr 17;9(4):e95415. doi: 10.1371/journal.pone.0095415. eCollection 2014.

Abstract

This study aimed to classify different emotional states by means of EEG-based functional connectivity patterns. Forty young participants viewed film clips that evoked the following emotional states: neutral, positive, or negative. Three connectivity indices, including correlation, coherence, and phase synchronization, were used to estimate brain functional connectivity in EEG signals. Following each film clip, participants were asked to report on their subjective affect. The results indicated that the EEG-based functional connectivity change was significantly different among emotional states. Furthermore, the connectivity pattern was detected by pattern classification analysis using Quadratic Discriminant Analysis. The results indicated that the classification rate was better than chance. We conclude that estimating EEG-based functional connectivity provides a useful tool for studying the relationship between brain activity and emotional states.

Publication types

  • Clinical Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Brain / metabolism
  • Brain Mapping / methods
  • Electroencephalography / methods*
  • Emotions / physiology*
  • Female
  • Humans
  • Male
  • Young Adult

Grants and funding

The authors would like to thank the National Science Council of the Republic of China, Taiwan for financially supporting this research (Contract No: NSC97-2420-H-002-220-MY3). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.