基于边界元法的SMS-LORETA --一种定位大脑皮层中多个同时活动源的先进方法
BEM-based SMS-LORETA - an advanced method to localize multiple simultaneously active sources in the cerebral cortex
摘要：
本文介绍了基于边界元法（BEM）的同步多源LORETA（SMS-LORETA）方法和性能数据。根据这些数据，该方法能够有效地定位多个同时活跃的神经源从头皮电位地形图自动。基于BEM的SMS-LORETA是一种完全解释sLORETA解决方案的程序，即，对于给定的头皮电位分布，它给出可识别源的数量以及它们的强度和方向。性能数据的结果，从模拟的无噪声和噪声污染的电位分布（地形），已获得通过基于边界元法的正向解决方案，其中一个，两个或三个同时主动偶极子随机选择关于他们的位置和极性的装置的许多分析。
英文摘要：
In this paper the method and performance data of 'Boundary Element Method (BEM)'-based SMS-LORETA (Simultaneous Multiple Sources LORETA) are presented. According to these data the method is capable of locating efficiently multiple simultaneously active neural sources from scalp potential topographies automatically. BEM-based SMS-LORETA is a procedure to fully interpret sLORETA solutions, i.e., with a given scalp potential distribution it gives the number of identifiable sources as well as their strength and orientation. Performance data result from numerous analyses of simulated noise-free and noise-contaminated potential distributions (topographies) that have been obtained by means of BEM-based forward solutions, where one, two or three simultaneously active dipoles were randomly chosen regarding their positions and polarity.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
