Amico Enrico, Bodart Olivier, Rosanova Mario, Gosseries Olivia, Heine Lizette, Van Mierlo Pieter, Martial Charlotte, Massimini Marcello, Marinazzo Daniele, Laureys Steven
1 Coma Science Group, Cyclotron Research Center & GIGA Research Center, University and University Hospital of Liège , Liège, Belgium .
2 Department of Data-Analysis, University of Ghent , Ghent, Belgium .
Brain Connect. 2017 Mar;7(2):84-97. doi: 10.1089/brain.2016.0462. Epub 2017 Mar 3.
Transcranial magnetic stimulation (TMS) in combination with neuroimaging techniques allows to measure the effects of a direct perturbation of the brain. When coupled with high-density electroencephalography (TMS/hd-EEG), TMS pulses revealed electrophysiological signatures of different cortical modules in health and disease. However, the neural underpinnings of these signatures remain unclear. Here, by applying multimodal analyses of cortical response to TMS recordings and diffusion magnetic resonance imaging (dMRI) tractography, we investigated the relationship between functional and structural features of different cortical modules in a cohort of awake healthy volunteers. For each subject, we computed directed functional connectivity interactions between cortical areas from the source-reconstructed TMS/hd-EEG recordings and correlated them with the correspondent structural connectivity matrix extracted from dMRI tractography, in three different frequency bands (α, β, γ) and two sites of stimulation (left precuneus and left premotor). Each stimulated area appeared to mainly respond to TMS by being functionally elicited in specific frequency bands, that is, β for precuneus and γ for premotor. We also observed a temporary decrease in the whole-brain correlation between directed functional connectivity and structural connectivity after TMS in all frequency bands. Notably, when focusing on the stimulated areas only, we found that the structure-function correlation significantly increases over time in the premotor area controlateral to TMS. Our study points out the importance of taking into account the major role played by different cortical oscillations when investigating the mechanisms for integration and segregation of information in the human brain.
经颅磁刺激(TMS)与神经成像技术相结合,能够测量大脑直接扰动的影响。当与高密度脑电图(TMS/hd-EEG)结合使用时,TMS脉冲揭示了健康和疾病状态下不同皮质模块的电生理特征。然而,这些特征的神经基础仍不清楚。在这里,通过对TMS记录的皮质反应和扩散磁共振成像(dMRI)纤维束成像进行多模态分析,我们在一组清醒的健康志愿者中研究了不同皮质模块的功能和结构特征之间的关系。对于每个受试者,我们从源重建的TMS/hd-EEG记录中计算皮质区域之间的定向功能连接相互作用,并将它们与从dMRI纤维束成像中提取的相应结构连接矩阵相关联,在三个不同频段(α、β、γ)和两个刺激部位(左楔前叶和左运动前区)进行分析。每个受刺激区域似乎主要通过在特定频段上被功能诱发来对TMS做出反应,即楔前叶为β频段,运动前区为γ频段。我们还观察到,在所有频段中,TMS后定向功能连接和结构连接之间的全脑相关性暂时下降。值得注意的是,仅关注受刺激区域时,我们发现与TMS对侧的运动前区中,结构-功能相关性随时间显著增加。我们的研究指出,在研究人类大脑中信息整合和分离机制时,考虑不同皮质振荡所起的主要作用非常重要。