Drug Effect on EEG Connectivity Assessed by Linear and Nonlinear Couplings
Drug Effect on EEG Connectivity Assessed by Linear and Nonlinear Couplings
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DOI：
10.1002/hbm.20881
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发表时间：
2010-03-01
影响因子：
4.8
通讯作者：
Barbanoj, Manel J.
中科院分区：
文献类型：
--
作者：
Alonso, Joan F.;Mananas, Miguel A.;Barbanoj, Manel J.
人类脑电图（EEG）的定量分析是评估精神药理学药物的重要方法。尽管不同药物类别对脑电图频谱的影响已为人所知，但大脑位置之间的相互作用仍不清楚。在这项工作中，应用交叉互信息函数和适当的替代数据来评估脑电图信号之间的线性和非线性耦合。主要目标是使用交叉安慰剂对照设计来评估阿普唑仑对健康志愿者清醒期间大脑连接的药理作用。选择 85 对 EEG 导联进行分析，并评估头皮前部、中央和后部区域内的连接性。还测量了这些区域之间的连通性和半球间的连通性。结果表明，与安慰剂相比，阿普唑仑在信息传递方面引起脑电图连接性的显着变化。根据统计特征，趋势是相反的：线性连接性减少和非线性耦合增加。这些影响通常遍布整个头皮。线性变化与药物血药浓度呈负相关，非线性变化与药物血药浓度呈正相关；后者表现出更高的相关系数。线性和非线性方法的使用揭示了评估脑电图连接变化的重要性，因为这可以提供有关精神药理学效应的有趣信息。 Hum Brain Mapp 31:487-497, 2010。(C) 2009 Wiley-Liss，hic。
Quantitative analysis of human electroencephalogram (EEG) is a valuable method for evaluating psychopharmacological agents. Although the effects of different drug classes on EEG spectra are already known, interactions between brain locations remain unclear. In this work, cross mutual information function and appropriate surrogate data were applied to assess linear and nonlinear couplings between EEG signals. The main goal was to evaluate the pharmacological effects of alprazolam on brain connectivity during wakefulness in healthy volunteers using a cross-over, placebo-controlled design. Eighty-five pairs of EEG leads were selected for the analysis, and connectivity was evaluated inside anterior, central, and posterior zones of the scalp. Connectivity between these zones and interhemispheric connectivity were also measured. Results showed that alprazolam induced significant changes in EEG connectivity in terms of information transfer in comparison with placebo. Trends were opposite depending on the statistical characteristics: decreases in linear connectivity and increases in nonlinear couplings. These effects were generally, spread over the entire scalp. Linear changes were negatively correlated, and nonlinear changes were positively correlated with drug plasma concentrations; the latter showed higher correlation coefficients. The use of both linear and nonlinear approaches revealed the importance of assessing changes in EEG connectivity as this can provide interesting information about psychopharmacological effects. Hum Brain Mapp 31:487-497, 2010. (C) 2009 Wiley-Liss, hic.