Epilepsy Program, Department of Neurology, Hospital Clínic, Neuroscience Institute, CP 08036, Barcelona, Spain.
Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden.
Cereb Cortex. 2020 Apr 14;30(4):2338-2357. doi: 10.1093/cercor/bhz243.
Focal epilepsy can be conceptualized as a network disorder, and the functional epileptic network can be described as a complex system of multiple brain areas that interact dynamically to generate epileptic activity. However, we still do not fully understand the functional architecture of epileptic networks. We studied a cohort of 21 patients with extratemporal focal epilepsy. We used independent component analysis of functional magnetic resonance imaging (fMRI) data. In order to identify the epilepsy-related components, we examined the general linear model-derived electroencephalography-fMRI (EEG-fMRI) time courses associated with interictal epileptic activity as intrinsic hemodynamic epileptic biomarkers. Independent component analysis revealed components related to the epileptic time courses in all 21 patients. Each epilepsy-related component described a network of spatially distributed brain areas that corresponded to the specific epileptic network in each patient. We also provided evidence for the interaction between the epileptic activity generated at the epileptic network and the physiological resting state networks. Our findings suggest that independent component analysis, guided by EEG-fMRI epileptic time courses, have the potential to define the functional architecture of the epileptic network in a noninvasive way. These data could be useful in planning invasive EEG electrode placement, guiding surgical resections, and more effective therapeutic interventions.
局灶性癫痫可以被概念化为一种网络障碍,而功能性癫痫网络可以被描述为一个由多个大脑区域组成的动态相互作用的复杂系统,以产生癫痫活动。然而,我们仍然不完全了解癫痫网络的功能结构。我们研究了 21 名颞叶外局灶性癫痫患者的队列。我们使用功能磁共振成像(fMRI)数据的独立成分分析。为了识别与癫痫相关的成分,我们检查了与间发性癫痫活动相关的基于广义线性模型的脑电图-fMRI(EEG-fMRI)时间序列,作为内在血液动力学癫痫生物标志物。独立成分分析显示,所有 21 名患者均与癫痫时间序列相关的成分。每个与癫痫相关的成分描述了一个由空间分布的大脑区域组成的网络,与每个患者的特定癫痫网络相对应。我们还提供了癫痫活动在癫痫网络中产生并与生理静息状态网络相互作用的证据。我们的研究结果表明,受 EEG-fMRI 癫痫时间序列指导的独立成分分析具有以非侵入性方式定义癫痫网络功能结构的潜力。这些数据可能有助于规划侵入性 EEG 电极放置、指导手术切除以及更有效的治疗干预。