DGAT: a dynamic graph attention neural network framework for EEG emotion recognition

DGAT: a dynamic graph attention neural network framework for EEG emotion recognition

IntroductionEmotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, current graph neural network models rely on predefined fixed adjacency matrices during training, which...

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Bibliographic Details
Main Authors: Shihang Ding, Kaixuan Wang, Wenhao Jiang, Cong Xu, Hongjian Bo, Lin Ma, Haifeng Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Psychiatry
Subjects:
EEG
emotion recognition
dynamic graph attention network
graph structure
affective computing
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1633860/full
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https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1633860/full

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