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EEG and MEG coherence: measures of functional connectivity at distinct spatial scales of neocortical dynamics

机译:脑电和脑电图的连贯性:在新的皮质动力学的不同空间尺度上的功能连接性的措施。

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摘要

We contrasted coherence estimates obtained with EEG, Laplacian, and MEG measures of synaptic activity using simulations with head models and simultaneous recordings of EEG and MEG. EEG coherence is often used to assess functional connectivity in human cortex. However, moderate to large EEG coherence can also arise simply by the volume conduction of current through the tissues of the head. We estimated this effect using simulated brain sources and a model of head tissues (CSF, skull, and scalp) derived from MRI. We found that volume conduction can elevate EEG coherence at all frequencies for moderately separated (< 10 cm) electrodes; a smaller elevation is observed with widely separated (> 20 cm) electrodes. This volume conduction effect was readily observed in experimental EEG at high frequencies (40-50 Hz). Cortical sources generating spontaneous EEG in this band are apparently uncorrelated. In contrast, while lower frequency EEG coherence appears to result from a mixture of volume conduction effects and genuine source coherence. Surface Laplacian EEG methods minimize the effect of volume conduction on coherence estimates by emphasizing sources at smaller spatial scales than unprocessed potentials (EEG). MEG coherence estimates are inflated at all frequencies by the field spread across the large distance between sources and sensors. This effect is most apparent at sensors separated by less than 15 cm in tangential directions along a surface passing through the sensors. In comparison to long-range (> 20 cm) volume conduction effects in EEG, widely spaced MEG sensors show smaller field spread effects, which is a potentially significant advantage. However, MEG coherence estimates reflect fewer sources at a smaller scale than EEG coherence and may only partially overlap EEG coherence. EEG, Laplacian, and MEG coherence emphasize different spatial scales and orientations of sources.
机译:我们对比了使用脑模型和同时记录EEG和MEG的脑电图,拉普拉斯和MEG的突触活动措施获得的一致性估计。脑电图一致性通常用于评估人类皮质的功能连接性。然而,通过头组织的电流的体积传导也可以简单地产生中等到较大的EEG相干性。我们使用模拟的脑源和源自MRI的头部组织(CSF,头骨和头皮)模型评估了这种效果。我们发现,对于中等间隔(<10 cm)的电极,体积传导可以提高所有频率下的脑电图相干性。使用相距较远(> 20厘米)的电极观察到较小的标高。在高频(40-50 Hz)的实验性EEG中很容易观察到这种体积传导效应。在该频带中产生自发性脑电图的皮层来源显然是不相关的。相比之下,虽然低频EEG相干性似乎是由体积传导效应和真正的源性相干性混合产生的。表面拉普拉斯EEG方法通过强调比未处理电势(EEG)更小的空间尺度的源,将体积传导对相干估计的影响最小化。通过在信号源和传感器之间的较大距离上分布的磁场,在所有频率上都增加了MEG相干估计。在沿穿过传感器的表面沿切线方向间隔小于15 cm的传感器中,此效果最为明显。与EEG中的远距离(> 20 cm)体积传导效应相比,相距较远的MEG传感器显示出较小的场扩散效应,这是潜在的重要优势。但是,MEG相干估计比EEG相干在更小的范围内反映了更少的来源,并且可能仅与EEG相干部分重叠。脑电图,拉普拉斯算术和MEG相干强调不同的空间尺度和源的方向。

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