Objective selection of epilepsy-related independent components from EEG data
Objective selection of epilepsy-related independent components from EEG data
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DOI：
10.1016/j.jneumeth.2015.10.003
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发表时间：
2016-01-30
影响因子：
3
通讯作者：
Figueiredo, Patricia
中科院分区：
文献类型：
--
作者：
Abreu, Rodolfo;Leite, Marco;Figueiredo, Patricia
背景资料：独立分量分析（伊卡）通常用于识别脑电图（EEG）数据中的感兴趣源，但根据具体应用，相关分量的选择仍然是一个悬而未决的问题。新方法：我们提出了一种新的方法，从功能磁共振成像（fMRI）采集过程中收集的EEG数据中客观选择癫痫相关的独立成分（IC），投影到独立元件上（PROJIC）。发作间期癫痫样放电（IED）识别的参考EEG数据集收集的MRI扫描仪外的专家神经生理学家，并将所得的平均IED投影到IC空间的EEG数据收集的同时与fMRI。IED投影的功率然后用于通知IC的k均值聚类算法，从而允许癫痫相关IC的分类。与现有方法的比较：PROJIC的性能与先前提出的用于感兴趣的EEG IC的客观选择的两种方法进行了比较，这两种方法基于IC与感兴趣事件的时空模板的显式相似性，结果：PROJIC方法对人工数据和真实的数据的拟合效果均优于其他方法（19个数据集收集自6名药物难治性局灶性癫痫患者），平均准确率为98.6%。我们的方法能够准确和客观地选择癫痫相关的IC，使其成为同步EEG的重要贡献。fMRI癫痫研究，在事件相关的EEG活动的分析更普遍的潜在应用，并在EEG伪影校正。(C)2015 Elsevier B.V.版权所有。
Background: Independent Component Analysis (ICA) is commonly used for the identification of sources of interest in electroencephalographic (EEG) data, but the selection of the relevant components remains an open issue depending on the specific application.New Method: We propose a novel approach for the objective selection of epilepsy-related independent components (ICs) from EEG data collected during functional Magnetic Resonance Imaging (fMRI) acquisitions, called PROJection onto Independent Components (PROJIC). Inter-ictal epileptiform discharges (IEDs) are identified on a reference EEG dataset collected outside the MRI scanner by an expert neurophysiologist, and the resulting average IED is projected onto the IC space of the EEG data collected simultaneously with fMRI. The power of the IED projection is then used to inform a k-means clustering algorithm of the ICs, allowing for the classification of epilepsy-related ICs.Comparison with existing methods: The performance of PROJIC was compared with two methods previously proposed for the objective selection of EEG ICs of interest, which are based on the explicit similarity of the ICs with spatio-temporal templates of the events of interest, instead of the projection power.Results: The proposed PROJIC method outperformed the others for both artificial and real data (19 datasets collected from 6 patients with drug-refractory focal epilepsy), with an average accuracy of 98.6%.Conclusions: The ability of our method to accurately and objectively select epilepsy-related ICs makes it an important contribution for simultaneous EEG-fMRI epilepsy studies, with potential applications in the analysis of event-related EEG activity more generally, and also in EEG artefact correction. (C) 2015 Elsevier B.V. All rights reserved.