Multisubject independent component analysis of fMRI: a decade of intrinsic networks, default mode, and neurodiagnostic discovery.
Multisubject independent component analysis of fMRI: a decade of intrinsic networks, default mode, and neurodiagnostic discovery.
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DOI：
10.1109/rbme.2012.2211076
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发表时间：
2012
影响因子：
17.6
通讯作者：
Adalı T
中科院分区：
文献类型：
--
作者：
Calhoun VD;Adalı T
自从在功能磁共振成像数据中发现功能连接（即，脑的空间上不同的区域之间的时间相关性）在该领域中已经进行了大量的工作。一个重要的焦点是使用网络而不是区域的概念来分析大脑连接。大约十年前，两个重要的研究领域从这个概念中产生出来。首先，Raichle提出了一种被称为“默认模式网络”的网络，该网络被称为“大脑功能的默认模式”。其次，多主体或群体独立成分分析（伊卡）提供了一种数据驱动的方法来研究大脑网络的属性，包括默认模式网络。在本文中，我们将提供一个集中的审查伊卡如何有助于研究的内在网络。我们将讨论伊卡组的一些方法学考虑，并强调研究大脑网络的多种分析方法。我们还将展示在患病大脑的默认模式和静息网络中观察到的一些差异的例子。总之，我们正处于激动人心的时刻，而且刚刚开始从丰富的功能性大脑网络和可用的分析方法中获益。
Since the discovery of functional connectivity in fMRI data (i.e., temporal correlations between spatially distinct regions of the brain) there has been a considerable amount of work in this field. One important focus has been on the analysis of brain connectivity using the concept of networks instead of regions. Approximately ten years ago two important research areas grew out of this concept. First, a network proposed to be “a default mode of brain function” since dubbed the default mode network was proposed by Raichle. Secondly, multi-subject or group independent component analysis (ICA) provided a data-driven approach to study properties of brain networks, including the default mode network. In this paper we will provide a focused review of how ICA has contributed to the study of intrinsic networks. We will discuss some methodological considerations for group ICA, and highlight multiple analytic approaches for studying brain networks. We will also show examples of some of the differences observed in the default mode and resting networks in the diseased brain. In summary, we are in exciting times and still just beginning to reap the benefits of the richness of functional brain networks as well as available analytic approaches.