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首页> 外文期刊>NeuroImage >Interactions between different EEG frequency bands and their effect on alpha-fMRI correlations.
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Interactions between different EEG frequency bands and their effect on alpha-fMRI correlations.

机译:不同的脑电图频带之间的相互作用及其对α-fMRI相关性的影响。

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In EEG/fMRI correlation studies it is common to consider the fMRI BOLD as filtered version of the EEG alpha power. Here the question is addressed whether other EEG frequency components may affect the correlation between alpha and BOLD. This was done comparing the statistical parametric maps (SPMs) of three different filter models wherein either the free or the standard hemodynamic response functions (HRF) were used in combination with the full spectral bandwidth of the EEG. EEG and fMRI were co-registered in a 30 min resting state condition in 15 healthy young subjects. Power variations in the delta, theta, alpha, beta and gamma bands were extracted from the EEG and used as regressors in a general linear model. Statistical parametric maps (SPMs) were computed using three different filter models, wherein either the free or the standard hemodynamic response functions (HRF) were used in combination with the full spectral bandwidth of the EEG. Results show that the SPMs of different EEG frequency bands, when significant, are very similar to that of the alpha rhythm. This is true in particular for the beta band, despite the fact that the alpha harmonics were discarded. It is shown that inclusion of EEG frequency bands as confounder in the fMRI-alpha correlation model has a large effect on the resulting SPM, in particular when for each frequency band the HRF is extracted from the data. We conclude that power fluctuations of different EEG frequency bands are mutually highly correlated, and that a multi frequency model is required to extract the SPM of the frequency of interest from EEG/fMRI data. When no constraints are put on the shapes of the HRFs of the nuisance frequencies, the correlation model looses so much statistical power that no correlations can be detected.
机译:在EEG / fMRI相关性研究中,通常将fMRI BOLD视为EEG alpha功效的过滤形式。这里的问题是其他脑电频率分量是否会影响alpha和BOLD之间的相关性。这是通过比较三种不同过滤器模型的统计参数图(SPM)来完成的,其中将自由或标准血液动力学响应函数(HRF)与EEG的整个频谱带宽结合使用。在15名健康的年轻受试者中,在30分钟的静息状态下对EEG和fMRI进行了共注册。从EEG中提取了δ,θ,α,β和γ谱带中的幂变化,并将其用作一般线性模型中的回归变量。使用三个不同的滤波器模型计算统计参数图(SPM),其中将自由或标准血液动力学响应函数(HRF)与EEG的整个频谱带宽结合使用。结果表明,不同脑电图频带的SPM显着时与阿尔法节律非常相似。尽管已删除了alpha谐波,但对于beta频段尤其如此。结果表明,在fMRI-alpha相关模型中将EEG频带作为混杂因素包括在内对所得SPM有很大影响,特别是当从数据中提取每个频带的HRF时。我们得出的结论是,不同EEG频带的功率波动相互高度相关,并且需要多频模型从EEG / fMRI数据中提取感兴趣频率的SPM。如果在讨厌的频率的HRF的形状上没有施加任何限制,则相关模型会失去太多的统计能力,从而无法检测到任何相关性。

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