Investigating ERP Brain Network for Alcohol-Dependent Patients Based on Phase-AmplitudeCoupling
Liu Xingping1, Wang Suogang2*
1(Department of Interventional Radiology, Chongqing University Three Gorges Hospital, Chongqing 404000, China) 2(School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China)
Abstract：In this study, we explored the application of complex network methods based on the phase-amplitude coupling of event-related potential brain network mechanisms for alcohol-dependent patients. The open-sourced event-related potentials generated by the delayed matching sample paradigm in 76 alcohol-dependent patients and 45 healthy controls were studied. After pre-processing the data, modulation index method was used to calculate the intensity of theta-gamma and alpha-gamma phase-amplitude coupling (TGC, AGC) among all paired channels to construct causal brain network, and then we measured the parameters of brain network graph theory when the network density was 0.3. In addition, the wavelet packet energy of theta, alpha, beta, gamma rhythms and fatigue factors were also calculated. The data was expressed in quartiles of 50% (25%, 75%). The results showed that there was a significant difference in the coupling intensity between the two groups with only non-target stimulation trials. The TGC and AGC between some paired channels of alcohol-dependent patients were significantly decreased (respectively 15.29%, 1.29%, all P<0.05), and the average coupling intensity was significantly decreased, especially for TGC [TGC: 0.014(0.011, 0.018) vs 0.012(0.010, 0.014), P=0.002; AGC: 0.012(0.010, 0.014) vs 0.011(0.010, 0.012), P=0.005]. In the TGC network, the characteristic path length [84.16(60.96, 110.33) vs 104.24(86.93, 118.98), P=0.005] and diameter [222.40(154.78, 254.39) vs 253.39(207.82, 307.99), P=0.003] of alcohol-dependent patients were significantly increased, and the average clustering coefficient [0.013(0.010, 0.019) vs 0.009(0.008, 0.012), P<0.001], global efficiency [0.014(0.011, 0.016) vs 0.011(0.010, 0.013), P<0.001], average local efficiency [0.017(0.013, 0.022) vs 0.013(0.011, 0.017), P<0.001] and transitivity [0.011(0.008, 0.016) vs 0.008(0.007, 0.010), P<0.001] were significantly decreased. The results of AGC network were like that of the TGC network, but the diameter difference was not statistically significant. The wavelet packet energy of theta, alpha, beta rhythms in most electrodes of alcohol-dependent patients were significantly decreased (respectively 95.08%、100%、50.82%, all P<0.05), also the fatigue factors in some electrodes were significantly decreased (45.90%, all P<0.05). When making judgement in non-target stimulation for alcohol-dependent patients, the cortical excitability increased, the inhibition control ability of brain decreased, the function separation and integration ability of TGC and AGC brain network decreased, and the topological organization of brain network was disordered.
刘兴平, 王索刚. 基于相位幅度耦合的酒精依赖患者ERP脑网络分析[J]. 中国生物医学工程学报, 2022, 41(2): 151-158.
Liu Xingping, Wang Suogang. Investigating ERP Brain Network for Alcohol-Dependent Patients Based on Phase-AmplitudeCoupling. Chinese Journal of Biomedical Engineering, 2022, 41(2): 151-158.
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