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The EEG microstate representation of discrete emotions.
Liu, Jin; Hu, Xin; Shen, Xinke; Lv, Zhao; Song, Sen; Zhang, Dan.
Afiliación
  • Liu J; Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China; Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China. Electronic address: jin-liu21@mails.tsinghua.edu.cn.
  • Hu X; Department of Psychology, Tsinghua University, Beijing 100084, China; Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China.
  • Shen X; Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China; Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China. Electronic address: sxk17@mails.tsinghua.edu.cn.
  • Lv Z; Anhui Province Key Labratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei 230601, China.
  • Song S; Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China; Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China. Electronic address: songsen@tsinghua.edu.cn.
  • Zhang D; Department of Psychology, Tsinghua University, Beijing 100084, China; Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China. Electronic address: dzhang@tsinghua.edu.cn.
Int J Psychophysiol ; 186: 33-41, 2023 04.
Article en En | MEDLINE | ID: mdl-36773887
ABSTRACT
Understanding how human emotions are represented in our brain is a central question in the field of affective neuroscience. While previous studies have mainly adopted a modular and static perspective on the neural representation of emotions, emerging research suggests that emotions may rely on a distributed and dynamic representation. The present study aimed to explore the EEG microstate representations for nine discrete emotions (Anger, Disgust, Fear, Sadness, Neutral, Amusement, Inspiration, Joy and Tenderness). Seventy-eight participants were recruited to watch emotion eliciting videos with their EEGs recorded. Multivariate analysis revealed that different emotions had distinct EEG microstate features. By using the EEG microstate features in the Neutral condition as the reference, the coverage of C, duration of C and occurrence of B were found to be the top-contributing microstate features for the discrete positive and negative emotions. The emotions of Disgust, Fear and Joy were found to be most effectively represented by EEG microstate. The present study provided the first piece of evidence of EEG microstate representation for discrete emotions, highlighting a whole-brain, dynamical representation of human emotions.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Electroencefalografía / Emociones Límite: Humans Idioma: En Revista: Int J Psychophysiol Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Electroencefalografía / Emociones Límite: Humans Idioma: En Revista: Int J Psychophysiol Año: 2023 Tipo del documento: Article