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Imaging haemodynamic changes related to seizures: comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG

机译:与癫痫发作有关的血流动力学影像学改变:基于脑电图的一般线性模型比较,功能磁共振成像和颅内脑电图的独立成分分析

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摘要

Background: Simultaneous EEG-fMRI can reveal haemodynamic changes associated with epileptic activity which may contribute to understanding seizure onset and propagation.udMethods: Nine of 83 patients with focal epilepsy undergoing pre-surgical evaluation had seizures during EEG-fMRI and analysed using three approaches, two based on the general linear model (GLM) and one using independent component analysis (ICA):udud1. EEGs were divided into up to three phases: early ictal EEG change, clinical seizure onset and late ictal EEG change and convolved with a canonical haemodynamic response function (HRF) (canonical GLM analysis).udud2. Seizures lasting three scans or longer were additionally modelled using a Fourier basis set across the entire event (Fourier GLM analysis).udud3. Independent component analysis (ICA) was applied to the fMRI data to identify ictal BOLD patterns without EEG.ududThe results were compared with intracranial EEG.udResults: udThe canonical GLM analysis revealed significant BOLD signal changes associated with seizures on EEG in 7/9 patients, concordant with the seizure onset zone in 4/7. The Fourier GLM analysis revealed changes in BOLD signal corresponding with the results of the canonical analysis in two patients. ICA revealed components spatially concordant with the seizure onset zone in all patients (8/9 confirmed by intracranial EEG).udConclusion: Ictal EEG-fMRI visualises plausible seizure related haemodynamic changes. The GLM approach to analysing EEG-fMRI data reveals localised BOLD changes concordant with the ictal onset zone when scalp EEG reflects seizure onset. ICA provides additional information when scalp EEG does not accurately reflect seizures and may give insight into ictal haemodynamics.
机译:背景:同时进行的EEG-fMRI可以揭示与癫痫活动相关的血液动力学变化,这可能有助于了解癫痫发作和传播。 ud方法:83例接受手术前评估的局灶性癫痫患者中有9例在EEG-fMRI期间出现癫痫发作,并使用三种方法进行了分析,其中两个基于通用线性模型(GLM),一个使用独立成分分析(ICA): ud ud1。脑电图分为三个阶段:早期发作性脑电图改变,临床发作发作和晚期发作性脑电图改变,并伴有典型的血液动力学反应功能(HRF)(典型的GLM分析)。 ud ud2。在整个事件中,使用傅立叶基础集对持续三次或更长时间的癫痫发作进行建模(Fourier GLM分析)。 ud ud3。将独立成分分析(ICA)应用于fMRI数据,以识别不伴有脑电图的发作性BOLD模式。 ud ud将结果与颅内EEG进行比较。 ud结果: ud典型GLM分析显示,与脑电图癫痫发作相关的BOLD信号显着改变。 7/9患者,与4/7中的发作发作区一致。傅立叶GLM分析显示两名患者的BOLD信号变化与规范分析结果相对应。 ICA揭示了所有患者的癫痫发作区在空间上相符的成分(颅内脑电图证实为8/9)。 ud结论:眼部EEG-fMRI可视化了癫痫发作相关的血流动力学变化。当头皮脑电图反映癫痫发作时,GLM方法分析EEG-fMRI数据可揭示与发作期区域一致的局部BOLD变化。当头皮脑电图不能准确反映癫痫发作并可能提供对眼动血流动力学的了解时,ICA提供了更多信息。

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