Research on Brain Functional Network and Lie Detection Based on Phase Lag Index
SI Hui-fang1, XIE Tian1, GAO Jun-feng1,2, GUAN Jin-an1, XIANG Zhou-zhou1, LAN Chang-you1, Qing Xun-hua1
1. School of Biomedical Engineering, South-Central University for Nationalities & Key Laboratory of Cognitive Science, State Ethnic Affairs Commission, Wuhan, Hubei 430074, China;
2. School of Life Science and Technology, UESTC, Chengdu, Sichuan 610054, China
Abstract：In the field of brain cognitive science,more researches begin to focus on the interdependence between different leads of EEG signals to study the overall cognitive function of the brain.The Phase Lag Index (PLI) can reduce the errors effectively caused by the volume conduction and has been widely adopted,however brain network research method based on graph theory was scarcely reported in lie detection field.In this study,the network topology of the EEG signals from 30 (innocent and guilty) subjects are analyzed.The network parameters are used as the discriminant indicators,and the experimental data are classified by using support vector machine.The study finds that the small world indexes have pretty significant statistical differences between two groups.Also,the classification system gets a higher lie-detection accuracy,which proves the validity of polygraph using PLI method and graph theory analysis.
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2018, Vol. 46 
