Ridley Ben, Wirsich Jonathan, Bettus Gaelle, Rodionov Roman, Murta Teresa, Chaudhary Umair, Carmichael David, Thornton Rachel, Vulliemoz Serge, McEvoy Andrew, Wendling Fabrice, Bartolomei Fabrice, Ranjeva Jean-Philippe, Lemieux Louis, Guye Maxime
Aix-Marseille Univ, CNRS, CRMBM UMR, 7339, Marseille, France.
APHM, Hôpitaux de la Timone, CEMEREM, Marseille, France.
Brain Topogr. 2017 Sep;30(5):639-655. doi: 10.1007/s10548-017-0551-5. Epub 2017 Feb 13.
For the first time in research in humans, we used simultaneous icEEG-fMRI to examine the link between connectivity in haemodynamic signals during the resting-state (rs) and connectivity derived from electrophysiological activity in terms of the inter-modal connectivity correlation (IMCC). We quantified IMCC in nine patients with drug-resistant epilepsy (i) within brain networks in 'healthy' non-involved cortical zones (NIZ) and (ii) within brain networks involved in generating seizures and interictal spikes (IZ1) or solely spikes (IZ2). Functional connectivity (h ) estimates for 10 min of resting-state data were obtained between each pair of electrodes within each clinical zone for both icEEG and fMRI. A sliding window approach allowed us to quantify the variability over time of h (vh ) as an indicator of connectivity dynamics. We observe significant positive IMCC for h and vh , for multiple bands in the NIZ only, with the strongest effect in the lower icEEG frequencies. Similarly, intra-modal h and vh were found to be differently modified as a function of different epileptic processes: compared to NIZ, [Formula: see text] was higher in IZ1, but lower in IZ2, while [Formula: see text] showed the inverse pattern. This corroborates previous observations of inter-modal connectivity discrepancies in pathological cortices, while providing the first direct invasive and simultaneous comparison in humans. We also studied time-resolved FC variability multimodally for the first time, finding that IZ1 shows both elevated internal [Formula: see text] and less rich dynamical variability, suggesting that its chronic role in epileptogenesis may be linked to greater homogeneity in self-sustaining pathological oscillatory states.
在人类研究中,我们首次使用同步颅内脑电图-功能磁共振成像(icEEG-fMRI)来研究静息状态(rs)下血流动力学信号的连通性与源自电生理活动的连通性之间的联系,即通过多模态连通性相关性(IMCC)进行研究。我们对9例耐药性癫痫患者的IMCC进行了量化,(i)在“健康”未受累皮质区(NIZ)的脑网络内,以及(ii)在参与产生癫痫发作和发作间期棘波的脑网络(IZ1)或仅产生棘波的脑网络(IZ2)内。对于icEEG和fMRI,在每个临床区域内的每对电极之间获取了10分钟静息状态数据的功能连通性(h )估计值。滑动窗口方法使我们能够将h 的随时间变化(vh )量化为连通性动态的指标。我们仅在NIZ中的多个频段观察到h 和vh 之间存在显著的正IMCC,在较低的icEEG频率中效应最强。同样,发现模态内的h 和vh 随着不同的癫痫过程而有不同的变化:与NIZ相比,IZ1中的[公式:见正文]较高,但IZ2中较低,而[公式:见正文]则呈现相反的模式。这证实了先前关于病理皮质中多模态连通性差异的观察结果,同时提供了人类首次直接侵入性和同步比较。我们还首次多模态地研究了时间分辨的功能连通性变异性,发现IZ1既显示出内部[公式:见正文]升高,又显示出动态变异性较少,这表明其在癫痫发生中的慢性作用可能与自持性病理振荡状态中更高的同质性有关。