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Related Concept Videos

Labeling Emotion01:20

Labeling Emotion

Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
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Identifying sex differences in EEG-based emotion recognition using graph convolutional network with attention

Dan Peng1, Wei-Long Zheng2, Luyu Liu2

  • 1RuiJin-Mihoyo Laboratory, Clinical Neuroscience Center, RuiJin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Rd., Shanghai 200020, People's Republic of China.

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|October 31, 2023
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Summary

Sex differences in emotional electroencephalography (EEG) patterns are evident across cultures and emotions. Emotion recognition models perform better when trained on same-sex data, highlighting the importance of sex in affective neuroscience.

Keywords:
EEGaffective brain–computer interfacedeep learningemotion recognitionsex differences

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Area of Science:

  • Neuroscience
  • Affective Computing
  • Biomedical Engineering

Background:

  • Sex differences in emotional experience are well-documented through self-reports and physiological measures.
  • However, distinct electroencephalography (EEG) neural patterns associated with sex differences in emotions remain largely unexplored.
  • Understanding these differences is crucial for advancing emotion recognition technologies and affective neuroscience.

Purpose of the Study:

  • To detect and characterize sex differences in emotional EEG patterns across diverse datasets and cultures.
  • To investigate how sex influences the performance of EEG-based emotion recognition models.
  • To provide physiological evidence for sex-specific emotion processing.

Main Methods:

  • Analysis of five public EEG datasets (SEED, SEED-IV, SEED-V, DEAP, DREAMER).
  • Systematic examination of sex-specific EEG patterns for multiple emotions (happy, sad, fearful, disgusted, neutral).
  • Implementation of deep learning models for sex-specific and cross-sex emotion recognition.

Main Results:

  • Significant sex differences in emotional EEG patterns were observed across various emotions and cultures.
  • Female emotional patterns were more stable, with distinct contrasts between happiness and negative emotions, while male patterns showed more balanced energy.
  • Key EEG features for females were concentrated frontally and temporally, whereas for males, they were more widespread.
  • Same-sex emotion recognition models consistently outperformed cross-sex models.

Conclusions:

  • The study provides novel physiological evidence for sex-specific emotional brain activation.
  • These findings underscore the importance of considering sex as a critical factor in affective research and the development of personalized medicine.
  • The results contribute to a deeper understanding of sex differences in emotion processing and neural correlates.