Adaptive analysis of fMRI data
Adaptive analysis of fMRI data
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DOI：
10.1016/s1053-8119(03)00077-6
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发表时间：
2003-07-01
期刊：
影响因子：
5.7
通讯作者：
Knutsson, H
中科院分区：
文献类型：
--
作者：
Friman, O;Borga, M;Knutsson, H
本文介绍了fMRI数据分析的新的和根本的改进。Central是一种被称为约束典型相关分析的技术，它可以被视为流行的一般线性模型方法的自然扩展和推广。空间基滤波器的概念，提出并证明是一个非常成功的自适应滤波的fMRI数据的方式。设计合适的血流动力学响应模型的一般方法也被提出，并纳入约束典型相关方法。结果表明，这些部分中的每一个显着提高了大脑活动的检测，计算时间以及实际使用的限制内，提供。(C)2003 Elsevier Science（美国）。All rights reserved.
This article introduces novel and fundamental improvements of fMRI data analysis. Central is a technique termed constrained canonical correlation analysis, which can be viewed as a natural extension and generalization of the popular general linear model method. The concept of spatial basis filters is presented and shown to be a very successful way of adaptively filtering the fMRI data. A general method for designing suitable hemodynamic response models is also proposed and incorporated into the constrained canonical correlation approach. Results that demonstrate how each of these parts significantly improves the detection of brain activity, with a computation time well within limits for practical use, are provided. (C) 2003 Elsevier Science (USA). All rights reserved.