Antelis Javier M, Minguez Javier
I3A and Department of informatics and Systems Engineering, University of Zaragoza, 50018 Zaragoza, Spain.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:77-80. doi: 10.1109/IEMBS.2009.5334969.
In this paper, we propose a solution to the EEG source localization problem considering its dynamic behavior. We assume a dipolar approach which makes the problem nonlinear. From the dynamic probabilistic model of the problem, we formulate the Extended Kalman Filter and Particle Filter solutions. In order to test the algorithms, we designed an experimental protocol based on error-related potentials. During the experiments, our dynamic solutions have allowed the estimation of sources which are varying in position and moment within the brain volume. Results confirm the activation of the anterior cingulate cortex which is the brain structure associated with error processing. These findings demonstrate the good performance of the dynamic solutions for estimating and tracking EEG neural generators.
在本文中，我们考虑脑电（EEG）源定位问题的动态行为提出了一种解决方案。我们采用偶极子方法，这使得该问题具有非线性。基于该问题的动态概率模型，我们制定了扩展卡尔曼滤波器和粒子滤波器解决方案。为了测试这些算法，我们基于错误相关电位设计了一个实验方案。在实验过程中，我们的动态解决方案能够估计脑容积内位置和时刻不断变化的源。结果证实了前扣带回皮层的激活，该脑区是与错误处理相关的脑结构。这些发现证明了动态解决方案在估计和跟踪EEG神经发生器方面的良好性能。
