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脑电和功能磁共振成像衍生的功能连接组同时显示出关联的动态。

Concurrent EEG- and fMRI-derived functional connectomes exhibit linked dynamics.

机构信息

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Department of Psychology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland.

出版信息

Neuroimage. 2020 Oct 1;219:116998. doi: 10.1016/j.neuroimage.2020.116998. Epub 2020 May 29.

Abstract

Long-range connectivity has become the most studied feature of human functional Magnetic Resonance Imaging (fMRI), yet the spatial and temporal relationship between its whole-brain dynamics and electrophysiological connectivity remains largely unknown. FMRI-derived functional connectivity exhibits spatial reconfigurations or time-varying dynamics at infraslow (<0.1Hz) speeds. Conversely, electrophysiological connectivity is based on cross-region coupling of fast oscillations (~1-100Hz). It is unclear whether such fast oscillation-based coupling varies at infraslow speeds, temporally coinciding with infraslow dynamics across the fMRI-based connectome. If so, does the association of fMRI-derived and electrophysiological dynamics spatially vary over the connectome across the functionally distinct electrophysiological oscillation bands? In two concurrent electroencephalography (EEG)-fMRI resting-state datasets, oscillation-based coherence in all canonical bands (delta through gamma) indeed reconfigured at infraslow speeds in tandem with fMRI-derived connectivity changes in corresponding region-pairs. Interestingly, irrespective of EEG frequency-band the cross-modal tie of connectivity dynamics comprised a large proportion of connections distributed across the entire connectome. However, there were frequency-specific differences in the relative strength of the cross-modal association. This association was strongest in visual to somatomotor connections for slower EEG-bands, and in connections involving the Default Mode Network for faster EEG-bands. Methodologically, the findings imply that neural connectivity dynamics can be reliably measured by fMRI despite heavy susceptibility to noise, and by EEG despite shortcomings of source reconstruction. Biologically, the findings provide evidence that contrast with known territories of oscillation power, oscillation coupling in all bands slowly reconfigures in a highly distributed manner across the whole-brain connectome.

摘要

长程连接已成为人类功能磁共振成像 (fMRI) 中研究最多的特征,但它的全脑动力学和电生理连通性之间的空间和时间关系在很大程度上仍然未知。FMRI 衍生的功能连接在亚慢(<0.1Hz)速度下表现出空间重新配置或时变动力学。相反,电生理连通性基于快速波动(~1-100Hz)的跨区域耦合。目前尚不清楚这种基于快速波动的耦合是否以亚慢速度变化,是否与 fMRI 连接组上的亚慢动力学同时发生。如果是这样,基于 fMRI 衍生和电生理动力学的关联是否会在功能上不同的电生理振荡带的连接组上随空间变化?在两个同时进行的脑电图 (EEG)-fMRI 静息状态数据集,所有典型频段(从 delta 到 gamma)的基于波动的相干性确实以亚慢速度重新配置,与相应区域对的 fMRI 衍生连接变化一致。有趣的是,无论 EEG 频段如何,连接动力学的跨模态联系都包含了连接组中分布在整个连接组中的很大一部分连接。然而,跨模态关联的相对强度存在频率特异性差异。这种关联在较慢的 EEG 频段的视觉到躯体运动连接中最强,在更快的 EEG 频段的默认模式网络连接中最强。从方法论上讲,这些发现意味着尽管 fMRI 容易受到噪声的影响,而 EEG 容易受到源重建缺点的影响,但仍可以可靠地测量神经连通性动力学。从生物学角度来看,这些发现提供了与已知振荡功率领域的证据相矛盾的证据,所有频段的振荡耦合都以高度分布式的方式在整个大脑连接组中缓慢重新配置。

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