Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland.
Neuroinformatics. 2013 Apr;11(2):159-73. doi: 10.1007/s12021-012-9161-2.
Epileptic seizures are due to the pathological collective activity of large cellular assemblies. A better understanding of this collective activity is integral to the development of novel diagnostic and therapeutic procedures. In contrast to reductionist analyses, which focus solely on small-scale characteristics of ictogenesis, here we follow a systems-level approach, which combines both small-scale and larger-scale analyses. Peri-ictal dynamics of epileptic networks are assessed by studying correlation within and between different spatial scales of intracranial electroencephalographic recordings (iEEG) of a heterogeneous group of patients suffering from pharmaco-resistant epilepsy. Epileptiform activity as recorded by a single iEEG electrode is determined objectively by the signal derivative and then subjected to a multivariate analysis of correlation between all iEEG channels. We find that during seizure, synchrony increases on the smallest and largest spatial scales probed by iEEG. In addition, a dynamic reorganization of spatial correlation is observed on intermediate scales, which persists after seizure termination. It is proposed that this reorganization may indicate a balancing mechanism that decreases high local correlation. Our findings are consistent with the hypothesis that during epileptic seizures hypercorrelated and therefore functionally segregated brain areas are re-integrated into more collective brain dynamics. In addition, except for a special sub-group, a highly significant association is found between the location of ictal iEEG activity and the location of areas of relative decrease of localised EEG correlation. The latter could serve as a clinically important quantitative marker of the seizure onset zone (SOZ).
癫痫发作是由于大细胞集合体的病理性集体活动引起的。更好地理解这种集体活动对于开发新的诊断和治疗程序至关重要。与仅关注癫痫发生的小规模特征的还原分析相反,我们采用系统水平的方法,将小规模和更大规模的分析结合起来。通过研究颅内脑电图(iEEG)记录的不同空间尺度之间和内部的相关性,评估癫痫网络的发作期动力学。通过单个 iEEG 电极记录的癫痫样活动通过信号导数来客观确定,然后对所有 iEEG 通道之间的相关性进行多元分析。我们发现,在癫痫发作期间,iEEG 探测到的最小和最大空间尺度上的同步性增加。此外,在中间尺度上观察到空间相关性的动态重新组织,这种组织在癫痫发作结束后仍然存在。有人提出,这种重新组织可能表明一种平衡机制,降低了局部的高相关性。我们的发现与以下假说一致,即在癫痫发作期间,超相关的、因此功能上分离的脑区被重新整合到更具集体性的脑动力学中。此外,除了一个特殊的亚组外,发作期 iEEG 活动的位置与局部 EEG 相关性相对降低的区域的位置之间存在高度显著的关联。后者可以作为发作起始区(SOZ)的重要临床定量标记物。