Research on Mutual Information-Based Brain Network and Lie Detection

被引：0

作者：

Peng S.-Y. ^{[1
]}

Zhou D. ^{[1
]}

Zhang J.-Q. ^{[1
]}

Wang Y. ^{[1
]}

Gao J.-F. ^{[1
]}

机构：

[1] Key Laboratory of Cognitive Science, School of Biomedical Engineering, South-Central University for Nationalities, Wuhan, 430074, Hubei

来源：

Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2019年 / 47卷 / 07期

关键词：

Brain networks; EEG; Feature extraction; Functional connectivity; Lie detection; Mutual information;

D O I：

10.3969/j.issn.0372-2112.2019.07.021

中图分类号：

学科分类号：

摘要：

The mutual information analysis is a method based on information theory to describe the information interaction between two signals.In view of the difficulty in extracting features of EEG signals in the current lie detection method and the circumstance that the analysis of the overall cognitive function of the brain were increasingly important in brain cognitive science research, this paper applied the mutual information analysis method to the field of EEG lie detection for the first time and quantified the correlation between the brain nodes and perform statistical analysis on the calculation results.The mutual information of the electrode pairs with significant differences in the two groups were selected as the classification features, on which the pattern recognition was performed, resulting in the accuracy rate of 99.67%.This result proves that the mutual information analysis is an effective brain functional connection analysis method, which provides a new way for lie detection research based on EEG signal connection analysis.In addition, the brain function network of both lying and honest subjects was also analyzed.The results show that when lying, the frontal, parietal, temporal, and occipital regions of the brain cooperate to achieve the lie function, and in the connection between the brain regions corresponding to the physical behavior and other brain regions, significant differences between the two groups was also shown.These above results will help us further reveal the neural activity mechanism of the lie. © 2019, Chinese Institute of Electronics. All right reserved.

引用

页码：1551 / 1556

页数：5

共 26 条

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