Dimension, reduction and spatiotemporal regression: Applications to neuroimaging

被引：0
|
作者：
Shedden, K [1 ]
Li, KC
机构：
[1] Univ Michigan, Dept Stat, Ann Arbor, MI 48109 USA
[2] Univ Calif Los Angeles, Dept Stat, Los Angeles, CA 90095 USA
来源：
COMPUTING IN SCIENCE & ENGINEERING | 2003年 / 5卷 / 05期
关键词：
D O I：
10.1109/MCISE.2003.1225858
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
One method for characterizing spatiotemporol variation in brain activity levels is based on the use of statistical dimension reduction. This reduction finds temporal components in data that best preserve the spatiotemporal regression structure. The method does this by suppressing more prominent waveforms that do not vary in a spatially predictable pattern.
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页码：30 / 36
页数：7
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