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Ghost interactions in MEG/EEG source space: A note of caution on inter-areal coupling measures

机译:Ghost互动在MEG / EEG源空间中:关于区域间耦合措施的注意事项

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When combined with source modeling, magneto-(MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase-and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or "ghost" interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations.
机译:当与源建模结合时,磁化(MEG)和脑电图(EEG)可用于研究皮质过程中的远程相互作用,非侵入性。然而,通过瞬时场地扩展和体积传导来阻碍这种面积间连通性的估计,其在皮质电流估计中人为地引入线性相关性并损伤源可分离性。为了克服标准相互作用测量固有的线性源混合的膨胀效应,已经提出了基于替代的基于幅度相关的连接措施,例如假想的相干性和正交化幅度相关性。根据定义对零滞后相关性不敏感,这些技术在识别不能归因于现场扩展或体积传导的相关性中越来越受欢迎。然而,我们在这里展示,虽然这些措施对线性混合的直接效应免疫,但它们仍然可以通过真实相互作用附近扩散的领域仍然揭示大量的虚假假阳性连接。这一基本问题影响了基于地区的基于区域的分析和全部连接的映射。最重要的是,除了定义和说明虚假的问题或“幽灵”相互作用的问题之外,我们通过广泛的模拟提供了对这种效果的严格量化。另外,我们进一步表明,信号混合也显着限制了神经元相和幅度相关的可分离性。我们得出结论,即使使用免疫与零滞后相关的措施,也必须在MEG / EEG源空间中的连接分析中仔细考虑杂散相关性。

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