图 书 馆
脑电和脑磁图源重建的逆方法Inverse Methods for EEG and MEG Source Reconstruction |
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| 课程网址: | http://videolectures.net/bbci2012_haufe_nolte_source_reconstructi... |
| 主讲教师: | Stefan Haufe; Guido Nolte |
| 开课单位: | 弗劳恩霍夫智能分析与信息系统研究所 |
| 开课时间: | 2012-12-03 |
| 课程语种: | 英语 |
| 中文简介: |  在本讲座中，我们回顾了用于EEG和MEG源重构的最流行的逆方法。逆方法可分为三种不同的类别：a）预定模型过多，b）偶极子场重建欠佳，并带有其他约束条件，c）扫描方法产生了神经活动的伪图像。我们将介绍以下方法的入门课程：1.偶极子模型，2.最小范数解和变量（L2，L1，混合范数，S FLEX），2.波束形成器（SAM，LCMV波束形成器，DICS）和4。子空间方法（MUSIC和RAP MUSIC）。本讲座的目的是解释这些方法背后的主要概念，并说明大多数模拟数据中的各自优缺点。 |
| 课程简介: | In this lecture we review the most popular inverse methods for EEG and MEG source reconstruction. Inverse methods can be divided into three different catagories: a) overdetermined models, b) underdetermined dipole field reconstructions with additional constraints, and c) scanning methods resulting in pseudoimages of neural activity. We will present an introductory course into the following methods: 1. Dipole models, 2. Minimum norm solutions and variants (L2, L1, mixed norms, S-FLEX), 2. Beamformers (SAM, LCMV-beamformer, DICS) , and 4. subspace methods (MUSIC and RAP-MUSIC). The aim of this lecture is to explain the main concepts behind these methods, and to illustrate respective strengths and weaknesses in mostly simulated data. |
| 关 键 词: | 模拟数据; 变量模型 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2021-03-20：zyk |
| 最后编审: | 2021-05-14：yumf |
| 阅读次数: | 82 |