Consistency of EEG source localization and connectivity estimates
Consistency of EEG source localization and connectivity estimates
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DOI：
10.1016/j.neuroimage.2017.02.076
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发表时间：
2017-05-15
期刊：
影响因子：
5.7
通讯作者：
Haufe, Stefan
中科院分区：
文献类型：
--
作者：
Mahjoory, Keyvan;Nikulin, Vadim V.;Haufe, Stefan
由于脑电图逆问题没有唯一的解决方案，因此从脑电图重建的源及其连接属性取决于正向和逆向建模参数，例如解剖模板和电模型的选择、对源的先前假设以及进一步的实现细节。为了将源连通性分析用作可靠的研究工具，需要在更广泛的标准估计例程中保持稳定性。使用两项研究中获得的 N=65 名参与者的静息态脑电图记录，我们首次全面评估了两个解剖模板（ICBM152 和 Colin27）、三个电模型（BEM、FEM 和球谐扩展）、三个反演方法（WMNE、eLORETA 和 LCMV）以及三个软件实现（Brainstorm、Fieldtrip 和我们自己的工具箱）的脑电图源定位和功能/有效连接指标的一致性。研究发现，在整个重建流程中，源定位比随后的功能连接估计更稳定，而有效连接估计则最不一致。所有结果相对不受电头模型选择的影响，而逆方法和源成像包的选择引起了相当大的变化。特别是，一方面 LCMV 波束形成器解决方案与另一方面 eLORETA/WMNE 分布式逆解决方案之间发现了相对较强的差异。我们还观察到，当比较研究之间、个体参与者内部以及个体参与者之间的结果时，一致性逐渐下降。为了在面对观察到的变异性时提供可靠的发现，需要涉及交互脑源的额外模拟。同时，我们鼓励使用多个源成像程序验证所获得的结果。
As the EEG inverse problem does not have a unique solution, the sources reconstructed from EEG and their connectivity properties depend on forward and inverse modeling parameters such as the choice of an anatomical template and electrical model, prior assumptions on the sources, and further implementational details. In order to use source connectivity analysis as a reliable research tool, there is a need for stability across a wider range of standard estimation routines. Using resting state EEG recordings of N=65 participants acquired within two studies, we present the first comprehensive assessment of the consistency of EEG source localization and functional/effective connectivity metrics across two anatomical templates (ICBM152 and Colin27), three electrical models (BEM, FEM and spherical harmonics expansions), three inverse methods (WMNE, eLORETA and LCMV), and three software implementations (Brainstorm, Fieldtrip and our own toolbox). Source localizations were found to be more stable across reconstruction pipelines than subsequent estimations of functional connectivity, while effective connectivity estimates where the least consistent. All results were relatively unaffected by the choice of the electrical head model, while the choice of the inverse method and source imaging package induced a considerable variability. In particular, a relatively strong difference was found between LCMV beamformer solutions on one hand and eLORETA/WMNE distributed inverse solutions on the other hand. We also observed a gradual decrease of consistency when results are compared between studies, within individual participants, and between individual participants. In order to provide reliable findings in the face of the observed variability, additional simulations involving interacting brain sources are required. Meanwhile, we encourage verification of the obtained results using more than one source imaging procedure.