Exploratory fMRI analysis by autocorrelation maximization

被引：107

作者：

Friman, O ^{[1
]}

Borga, M

Lundberg, P

Knutsson, H

机构：

[1] Linkoping Univ Hosp, Dept Biomed Engn, S-58185 Linkoping, Sweden

[2] Linkoping Univ Hosp, Dept Radiat Phys, S-58185 Linkoping, Sweden

[3] Linkoping Univ Hosp, Dept Diagnost Radiol, S-58185 Linkoping, Sweden

来源：

NEUROIMAGE | 2002年 / 16卷 / 02期

关键词：

D O I：

10.1006/nimg.2002.1067

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

A novel and computationally efficient method for exploratory analysis of functional MRI data is presented. The basic idea is to reveal underlying components in the fMRI data that have maximum autocorrelation. The tool for accomplishing this task is Canonical Correlation Analysis. The relation to Principal Component Analysis and Independent Component Analysis is discussed and the performance of the methods is compared using both simulated and real data. (C) 2002 Elsevier Science (USA).

引用

页码：454 / 464

页数：11

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