Functional Graph Contrastive Learning of Hyperscanning EEG Reveals Emotional Contagion Evoked by Stereotype-Based Stressors
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Abstract (arXiv)
This study delves into the intricacies of emotional contagion and its impact on performance within dyadic interactions. Specifically, it focuses on the context of stereotype-based stress (SBS) during collaborative problem-solving tasks among female pairs. Through an exploration of emotional contagion, this study seeks to unveil its underlying mechanisms and effects. Leveraging EEG-based hyperscanning technology, we introduced an innovative approach known as the functional Graph Contrastive Learning (fGCL), which extracts subject-invariant representations of neural activity patterns from feedback trials. These representations are further subjected to analysis using the Dynamic Graph Classification (DGC) model, aimed at dissecting the process of emotional contagion along three independent temporal stages. The results underscore the substantial role of emotional contagion in shaping the trajectories of participants' performance during collaborative tasks in the presence of SBS conditions. Overall, our research contributes invaluable insights into the neural underpinnings of emotional contagion, thereby enriching our comprehension of the complexities underlying social interactions and emotional dynamics.
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References · 5
- 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 12,049
- 2016Convolutional Neural Networks on Graphs with Fast Localized Spectral Filteringcited by 2,089
- 2018Towards Sparse Hierarchical Graph Classifierscited by 100
- 2021Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognitioncited by 60
- 2021EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signalscited by 28
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