Muthuraman Muthuraman, Hellriegel Helge, Hoogenboom Nienke, Anwar Abdul Rauf, Mideksa Kidist Gebremariam, Krause Holger, Schnitzler Alfons, Deuschl Günther, Raethjen Jan
Department of Neurology, Christian-Albrechts-University, Kiel, Germany.
Department of Neurology, Heinrich-Heine University, Dusseldorf, Germany.
PLoS One. 2014 Mar 11;9(3):e91441. doi: 10.1371/journal.pone.0091441. eCollection 2014.
Electroencephalography (EEG) and magnetoencephalography (MEG) are the two modalities for measuring neuronal dynamics at a millisecond temporal resolution. Different source analysis methods, to locate the dipoles in the brain from which these dynamics originate, have been readily applied to both modalities alone. However, direct comparisons and possible advantages of combining both modalities have rarely been assessed during voluntary movements using coherent source analysis. In the present study, the cortical and sub-cortical network of coherent sources at the finger tapping task frequency (2-4 Hz) and the modes of interaction within this network were analysed in 15 healthy subjects using a beamformer approach called the dynamic imaging of coherent sources (DICS) with subsequent source signal reconstruction and renormalized partial directed coherence analysis (RPDC). MEG and EEG data were recorded simultaneously allowing the comparison of each of the modalities separately to that of the combined approach. We found the identified network of coherent sources for the finger tapping task as described in earlier studies when using only the MEG or combined MEG+EEG whereas the EEG data alone failed to detect single sub-cortical sources. The signal-to-noise ratio (SNR) level of the coherent rhythmic activity at the tapping frequency in MEG and combined MEG+EEG data was significantly higher than EEG alone. The functional connectivity analysis revealed that the combined approach had more active connections compared to either of the modalities during the finger tapping (FT) task. These results indicate that MEG is superior in the detection of deep coherent sources and that the SNR seems to be more vital than the sensitivity to theoretical dipole orientation and the volume conduction effect in the case of EEG.
脑电图（EEG）和脑磁图（MEG）是两种能够以毫秒级时间分辨率测量神经元活动的方法。不同的源分析方法，即从大脑中定位这些活动起源的偶极子的方法，已分别广泛应用于这两种方法。然而，在使用相干源分析的自愿运动过程中，很少有人评估将这两种方法结合使用的直接比较和潜在优势。在本研究中，使用一种称为相干源动态成像（DICS）的波束形成方法，对15名健康受试者在手指敲击任务频率（2-4Hz）下的相干源皮质和皮质下网络以及该网络内的相互作用模式进行了分析，随后进行了源信号重建和重新归一化偏相干分析（RPDC）。同时记录了MEG和EEG数据，以便将每种方法分别与联合方法进行比较。我们发现，在仅使用MEG或联合使用MEG+EEG时，如早期研究所描述的那样，确定了手指敲击任务的相干源网络，而单独的EEG数据未能检测到单个皮质下源。MEG和联合MEG+EEG数据中敲击频率下相干节律活动的信噪比（SNR）水平显著高于单独的EEG。功能连接性分析表明，在手指敲击（FT）任务期间，联合方法比任何一种方法都有更多活跃连接。这些结果表明，MEG在检测深部相干源方面更具优势，并且在EEG的情况下，SNR似乎比理论偶极子方向的敏感性和容积传导效应更重要。
