MEG-SIM: A Web Portal for Testing MEG Analysis Methods using Realistic Simulated and Empirical Data
MEG-SIM: A Web Portal for Testing MEG Analysis Methods using Realistic Simulated and Empirical Data
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DOI：
10.1007/s12021-011-9132-z
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发表时间：
2012-04-01
期刊：
影响因子：
3
通讯作者：
Stephen, J. M.
中科院分区：
文献类型：
--
作者：
Aine, C. J.;Sanfratello, L.;Stephen, J. M.
MEG和EEG以精确的时间分辨率测量大脑中的电生理活动。由于这种相对于基于非侵入性血液动力学的测量（fMRI、PET）的独特优势，血液动力学和电生理学技术的互补性质正变得越来越被广泛地认识到（例如，人类连接组计划）。然而，用于解决MEG和EEG的逆问题的可用分析方法尚未被比较和标准化到它们用于fMRI/PET的程度。许多因素，包括MEG/EEG逆问题的解的非唯一性，导致了多种分析技术，这些技术尚未在一致的数据集上进行测试，使得技术的直接比较具有挑战性（或不可能）。由于每一种方法都有自己的优点和缺点，因此将其量化是有益的。为此，我们宣布建立一个网站，其中载有大量用于测试目的的真实模拟数据（http：//cobre.mrn.org/megsim/）。在这里，我们介绍：1）逆向过程的基本类型的简要概述; 2）所创建的测试床的原理和描述;以及3）强调功能连接性的情况（例如，振荡活动），适用于各种分析，包括独立成分分析（伊卡）、格兰杰因果关系/定向传递函数和单次试验分析。
MEG and EEG measure electrophysiological activity in the brain with exquisite temporal resolution. Because of this unique strength relative to noninvasive hemodynamic-based measures (fMRI, PET), the complementary nature of hemodynamic and electrophysiological techniques is becoming more widely recognized (e.g., Human Connectome Project). However, the available analysis methods for solving the inverse problem for MEG and EEG have not been compared and standardized to the extent that they have for fMRI/PET. A number of factors, including the non-uniqueness of the solution to the inverse problem for MEG/EEG, have led to multiple analysis techniques which have not been tested on consistent datasets, making direct comparisons of techniques challenging (or impossible). Since each of the methods is known to have their own set of strengths and weaknesses, it would be beneficial to quantify them. Toward this end, we are announcing the establishment of a website containing an extensive series of realistic simulated data for testing purposes (http://cobre.mrn.org/megsim/). Here, we present: 1) a brief overview of the basic types of inverse procedures; 2) the rationale and description of the testbed created; and 3) cases emphasizing functional connectivity (e.g., oscillatory activity) suitable for a wide assortment of analyses including independent component analysis (ICA), Granger Causality/Directed transfer function, and single-trial analysis.