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使用电流密度最小化方法进行源定位。

Source localization using a current-density minimization approach.

作者信息

Miga Michael I, Kerner Todd E, Darcey Terrance M

机构信息

Vanderbilt University, Department of Biomedical Engineering, Nashville, TN 37235, USA.

出版信息

IEEE Trans Biomed Eng. 2002 Jul;49(7):743-5. doi: 10.1109/TBME.2002.1010860.

Abstract

Determining the location of cortical activity from electroencephalographic (EEG) data is important clinically. In this paper, a method is presented which uses the powerful optimization method of simulated annealing in conjunction with a finite-element-based model of the search domain for single-time slice solution of the EEG-inverse problem. The algorithm highlights a new objective function based on the current-density boundary integral associated with the finite-element formulation as the basis for parameter optimization. In two-dimensional experiments in a shallow tank containing saline, single dipoles are located within 2 mm. Simulations studying the algorithms response to structured noise are also presented. The new objective function is shown to take advantage of the natural framework associated with finite-elements and the results suggest that the approach is capable of resolving dipole locations in simulations and experiments.

摘要

从脑电图(EEG)数据确定皮层活动的位置在临床上很重要。本文提出了一种方法,该方法将强大的模拟退火优化方法与基于有限元的搜索域模型相结合,用于脑电图逆问题的单时间切片求解。该算法突出了基于与有限元公式相关的电流密度边界积分的新目标函数,作为参数优化的基础。在装有盐水的浅水箱中进行的二维实验中,单个偶极子的定位误差在2毫米以内。还给出了研究该算法对结构化噪声响应的模拟。新目标函数显示出利用了与有限元相关的自然框架,结果表明该方法能够在模拟和实验中解析偶极子位置。

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