EEG-Based Micro-Expression Recognition: Flexible Brain Network Reconfiguration Supporting Micro-Expressions Under Positive Emotion

Jiejia Chen,1,2,* Xingcong Zhao,1,3,* Zhiheng Xiong,4 Guangyuan Liu1,2 1School of Electronic and Information Engineering, Southwest University, Chongqing, People’s Republic of China; 2Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing, People’s Republic of China; 3West China Institute of Children’s Brain and Cognition, Chongqing University of Education, Chongqing, People’s Republic of China; 4School of Humanities, Southeast University, Nanjing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Guangyuan Liu, Email [email protected]: Micro-expression recognition is valuable in clinical, security, judicial, economic, educational, and human-computer interaction fields. Electroencephalography (EEG)-based micro-expression recognition has gained attention for its objectivity and resistance to interference, unlike image-based methods. However, the neural mechanisms of micro-expressions remain unclear, limiting the development of EEG-based recognition technology.Methods: We explored the brain reorganization mechanisms of micro-expressions (compared with macro-expressions and neutral expressions) under positive emotions across global networks, functional network modules, and hub brain regions using EEG, graph theory analysis, and functional connectivity.Results: In global network, micro-expressions demonstrated higher network efficiency, clustering coefficient, and local efficiency, along with shorter average path lengths. In functional network modules, micro-expressions enhanced connectivity between the bilateral superior frontal gyrus (SFG), anterior cingulate cortex, and ventromedial prefrontal cortex (cognitive control), as well as between the left orbitofrontal cortex (OFC), temporal pole (TP), and inferior frontal gyrus (emotional processing). In hub brain regions, micro-expressions increased the hub centrality, information transmission efficiency, and local clustering of bilateral SFG, left OFC, left TP, and left Broca’s area.Conclusion: Micro-expressions require more efficient global communication and specialized emotion and cognitive control modules. Key hub regions supporting positive micro-expressions include the bilateral SFG (inhibitory control), left OFC and TP (emotion processing), and left Broca’s area (language processing).Keywords: macro-expressions, neutral expressions, electroencephalography, EEG, graph theory, functional connectivity

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-04-01
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

EEG-Based Micro-Expression Recognition: Flexible Brain Network Reconfiguration Supporting Micro-Expressions Under Positive Emotion

SHILAP Revista de lepidopterología
Emotion and Mood Recognition
article

EEG-Based Micro-Expression Recognition: Flexible Brain Network Reconfiguration Supporting Micro-Expressions Under Positive Emotion

article en

Abstract

Jiejia Chen,1,2,* Xingcong Zhao,1,3,* Zhiheng Xiong,4 Guangyuan Liu1,2 1School of Electronic and Information Engineering, Southwest University, Chongqing, People’s Republic of China; 2Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing, People’s Republic of China; 3West China Institute of Children’s Brain and Cognition, Chongqing University of Education, Chongqing, People’s Republic of China; 4School of Humanities, Southeast University, Nanjing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Guangyuan Liu, Email [email protected]: Micro-expression recognition is valuable in clinical, security, judicial, economic, educational, and human-computer interaction fields. Electroencephalography (EEG)-based micro-expression recognition has gained attention for its objectivity and resistance to interference, unlike image-based methods. However, the neural mechanisms of micro-expressions remain unclear, limiting the development of EEG-based recognition technology.Methods: We explored the brain reorganization mechanisms of micro-expressions (compared with macro-expressions and neutral expressions) under positive emotions across global networks, functional network modules, and hub brain regions using EEG, graph theory analysis, and functional connectivity.Results: In global network, micro-expressions demonstrated higher network efficiency, clustering coefficient, and local efficiency, along with shorter average path lengths. In functional network modules, micro-expressions enhanced connectivity between the bilateral superior frontal gyrus (SFG), anterior cingulate cortex, and ventromedial prefrontal cortex (cognitive control), as well as between the left orbitofrontal cortex (OFC), temporal pole (TP), and inferior frontal gyrus (emotional processing). In hub brain regions, micro-expressions increased the hub centrality, information transmission efficiency, and local clustering of bilateral SFG, left OFC, left TP, and left Broca’s area.Conclusion: Micro-expressions require more efficient global communication and specialized emotion and cognitive control modules. Key hub regions supporting positive micro-expressions include the bilateral SFG (inhibitory control), left OFC and TP (emotion processing), and left Broca’s area (language processing).Keywords: macro-expressions, neutral expressions, electroencephalography, EEG, graph theory, functional connectivity

SHILAP Revista de lepidopterología
Openalex Percentile: Top 44%
Emotion and Mood Recognition
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

EEG-Based Micro-Expression Recognition: Flexible Brain Network Reconfiguration Supporting Micro-Expressions Under Positive Emotion · SHILAP Revista de lepidopterología (2025) | TGRS Research Map | TGRS