Suppr超能文献

一种人类癫痫发作的系统级研究方法。

A systems-level approach to human epileptic seizures.

机构信息

Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland.

出版信息

Neuroinformatics. 2013 Apr;11(2):159-73. doi: 10.1007/s12021-012-9161-2.

Abstract

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).

摘要

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。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验