Review of EEG Affective Recognition with a Neuroscience Perspective
Rosary Yuting Lim1, Wai-Cheong Lincoln Lew1,2, Kai Keng Ang1,2
1Institute for Infocomm Research, Agency for Science, Technology and Research, A*STAR, 1 Fusionopolis Way, #21-01 Connexis, Singapore 138632, Singapore.
Brain Sciences
|April 27, 2024
Summary
This review explores how brain
Area of Science:
- Neuroscience
- Affective Computing
- Computational Neuroscience
Background:
- Emotions are integral to human experience, influencing cognition and behavior.
- Neuroscience and affective computing have extensively studied emotion recognition.
- Electroencephalography (EEG)-based emotion recognition is a growing field.
Purpose of the Study:
- To review neuroscientific evidence for emotion generation in subcortical brain structures.
- To connect neuroscience findings with current affective computing models for emotion recognition.
- To evaluate biologically inspired modeling for advancing EEG-based emotion recognition.
Main Methods:
- Literature review of neuroscience and affective computing research.
- Analysis of neural circuitry involved in emotion processing.
- Examination of EEG data collection and analysis in affective computing.
Main Results:
- Emotions may arise from neural activities in subcortical structures.
- Neuroscience provides a basis for developing affective computing models.
- EEG-based emotion recognition models can be informed by neural underpinnings.
Conclusions:
- Biologically inspired models hold promise for advancing EEG-based emotion recognition.
- Integrating neuroscience and affective computing can enhance emotion recognition technologies.
- Further research is needed to fully leverage neural insights for artificial emotion recognition.
