Depressed MEG causality analysis based on polynomial kernel Granger causality
Jing Qian,
Wenpo Yao,
Dengxuan Bai,
Qiong Wang,
Shuwang Wang,
Ang Zhou,
Wei Yan,
Jun Wang
Affiliations
Jing Qian
School of Geographic and Biologic Information, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Wenpo Yao
School of Geographic and Biologic Information, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Dengxuan Bai
School of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
Qiong Wang
School of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
Shuwang Wang
School of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
Ang Zhou
Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China
Wei Yan
Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China
Jun Wang
School of Geographic and Biologic Information, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
In this study, we employ the Granger causality of a polynomial kernel to identify the coupling causality of depressed magnetoencephalography (MEG). We collect MEG under positive, neutral, and negative emotional stimuli and focus on the β-band activities. According to test results, depressed people display stronger left–right symmetrical interconnection in their prefrontal and occipital lobes under nonpositive stimuli(namely neutral and negative stimuli), indicating that they are more sensitive to nonpositive stimuli. The intensity of the right occipital information flow is higher in depressed people. We also see the Granger causality index increased in the occipital–frontal areas of depressed patients under negative stimuli. In general, detecting the polynomial kernel Granger causality of the MEG can effectively characterize the strength of the interconnected brain regions in depressed patients, which can be used as a clinical diagnosis aid.
