Accuracy of Two Dipolar Inverse Algorithms Applying Reciprocity for Forward Calculation

Päivi Laarne , Jari Hyttinen , Silke Dodel , Jaakko Malmivuo , Hannu Eskola
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引用次数: 32

Abstract

Two inverse algorithms were applied for solving the EEG inverse problem assuming a single dipole as a source model. For increasing the efficiency of the forward computations the lead field approach based on the reciprocity theorem was applied. This method provides a procedure to calculate the computationally heavy forward problem by a single solution for each EEG lead. A realistically shaped volume conductor model with five major tissue compartments was employed to obtain the lead fields of the standard 10–20 EEG electrode system and the scalp potentials generated by simulated dipole sources. A least-squares method and a probability-based method were compared in their performance to reproduce the dipole source based on the reciprocal forward solution. The dipole localization errors were 0 to 9 mm and 2 to 22 mm without and with added noise in the simulated data, respectively. The two different inverse algorithms operated mainly very similarly. The lead field method appeared applicable for the solution of the inverse problem and especially useful when a number of sources, e.g., multiple EEG time instances, must be solved.

应用互易进行正演计算的两种偶极逆算法的精度
以单偶极子为源模型,采用两种反算法求解脑电反问题。为了提高正演计算的效率,采用了基于互易定理的超前场法。该方法为计算计算量大的正演问题提供了一种方法。采用具有5个主要组织隔室的真实形状体积导体模型,获得了标准10-20脑电电极系统的引线场和模拟偶极源产生的头皮电位。比较了基于互反正解的最小二乘法和基于概率的方法再现偶极子源的性能。模拟数据中无噪声和有噪声的偶极子定位误差分别为0 ~ 9 mm和2 ~ 22 mm。这两种不同的逆算法的操作基本上非常相似。引线场法适用于求解逆问题,尤其适用于求解多个源,如多个EEG时间实例。
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