Paired MEG data set source localization using recursively applied and projected (RAP) MUSIC

被引：0
|
作者：
Ermer, JJ [1 ]
Mosher, JC [1 ]
Leahy, RM [1 ]
Huang, MX [1 ]
机构：
[1] Univ So Calif, Signal & Image Proc Lab, Los Angeles, CA 90089 USA
来源：
CONFERENCE RECORD OF THE THIRTY-SECOND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1 AND 2 | 1998年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An important class of experiments in functional brain mapping involves collecting pairs of data corresponding to separate 'Task' and 'Control' conditions. The data are then analyzed to determine what activity occurs during the Task experiment but not in the Control. Here we describe a new method for processing paired magnetoencephalographic (MEG) data sets using our Recursively Applied and Projected Multiple Signal Classification (RAP-MUSIC) algorithm. In this method the signal subspace of the Task data is projected against the orthogonal complement of the Control data signal subspace to obtain a subspace which describes activity unique to the Task. A (RAP-MUSIC) localization search is then performed on this projected data to localize the sources which are active in the Task but not in the Control data.
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收藏
页码：319 / 324
页数：6
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