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EEG-Based Micro-Expression Recognition: Flexible Brain Network Reconfiguration Supporting Micro-Expressions Under
Jiejia Chen1,2, Xingcong Zhao1,3, Zhiheng Xiong4
1School of Electronic and Information Engineering, Southwest University, Chongqing, People's Republic of China.
Psychology Research and Behavior Management
|April 7, 2025
Summary
Electroencephalography (EEG) reveals that micro-expressions, compared to macro-expressions, involve enhanced global brain network efficiency and specialized neural pathways for emotion and cognitive control. This deepens understanding of micro-expression neural mechanisms.
Area of Science:
- Neuroscience
- Cognitive Science
- Affective Computing
Background:
- Micro-expression recognition is crucial across various fields, including clinical, security, and human-computer interaction.
- Electroencephalography (EEG)-based recognition offers objectivity and interference resistance, but underlying neural mechanisms are poorly understood.
- Clarifying neural mechanisms is vital for advancing EEG-based micro-expression recognition technology.
Purpose of the Study:
- To investigate the brain reorganization mechanisms associated with micro-expressions versus macro- and neutral expressions.
- To analyze these mechanisms across global brain networks, functional network modules, and hub brain regions.
- To utilize EEG, graph theory analysis, and functional connectivity for this exploration.
Main Methods:
- Employed EEG to record brain activity during different expression types (micro, macro, neutral) under positive emotions.
- Applied graph theory analysis to assess network properties like efficiency, clustering, and path lengths.
- Utilized functional connectivity analysis to examine interactions within and between brain regions.
Main Results:
- Micro-expressions exhibited increased global network efficiency, clustering, and local efficiency, with shorter average path lengths.
- Enhanced connectivity was observed in modules related to cognitive control (SFG, ACC, vmPFC) and emotional processing (lOFC, TP, IFG).
- Hub regions like bilateral SFG, left OFC, left TP, and left Broca's area showed increased centrality and information transmission efficiency.
Conclusions:
- Micro-expressions necessitate more efficient global communication and specialized neural modules for emotion and cognitive control.
- Key brain regions supporting positive micro-expressions include bilateral SFG (inhibitory control), left OFC/TP (emotion processing), and left Broca's area (language processing).
- Findings provide insights into the neural underpinnings of micro-expressions, paving the way for improved EEG-based recognition.
