Esposito Fabrizio, Aragri Adriana, Pesaresi Ilaria, Cirillo Sossio, Tedeschi Gioacchino, Marciano Elio, Goebel Rainer, Di Salle Francesco
Department of Neuroscience, University of Naples Federico II, Naples, Italy.
Magn Reson Imaging. 2008 Sep;26(7):905-13. doi: 10.1016/j.mri.2008.01.045. Epub 2008 May 16.
Resting-state functional magnetic resonance imaging (RS-fMRI) is a technique used to investigate the spontaneous correlations of blood-oxygen-level-dependent signals across different regions of the brain. Using functional connectivity tools, it is possible to investigate a specific RS-fMRI network, referred to as "default-mode" (DM) network, that involves cortical regions deactivated in fMRI experiments with cognitive tasks. Previous works have reported a significant effect of aging on DM regions activity. Independent component analysis (ICA) is often used for generating spatially distributed DM functional connectivity patterns from RS-fMRI data without the need for a reference region. This aspect and the relatively easy setup of an RS-fMRI experiment even in clinical trials have boosted the combined use of RS-fMRI and ICA-based DM analysis for noninvasive research of brain disorders. In this work, we considered different strategies for combining ICA results from individual-level and population-level analyses and used them to evaluate and predict the effect of aging on the DM component. Using RS-fMRI data from 20 normal subjects and a previously developed group-level ICA methodology, we generated group DM maps and showed that the overall ICA-DM connectivity is negatively correlated with age. A negative correlation of the ICA voxel weights with age existed in all DM regions at a variable degree. As an alternative approach, we generated a distributed DM spatial template and evaluated the correlation of each individual DM component fit to this template with age. Using a "leave-one-out" procedure, we discuss the importance of removing the bias from the DM template-generation process.
静息态功能磁共振成像（RS-fMRI）是一种用于研究大脑不同区域血氧水平依赖信号自发相关性的技术。使用功能连接工具，可以研究一个特定的RS-fMRI网络，称为“默认模式”（DM）网络，该网络涉及在认知任务的fMRI实验中失活的皮质区域。先前的研究报告了衰老对DM区域活动有显著影响。独立成分分析（ICA）通常用于从RS-fMRI数据生成空间分布的DM功能连接模式，而无需参考区域。这一特点以及即使在临床试验中RS-fMRI实验相对容易设置，推动了RS-fMRI和基于ICA的DM分析在脑部疾病无创研究中的联合应用。在这项工作中，我们考虑了将个体水平和群体水平分析的ICA结果相结合的不同策略，并使用它们来评估和预测衰老对DM成分的影响。利用20名正常受试者的RS-fMRI数据和先前开发的群体水平ICA方法，我们生成了群体DM图谱，并表明整体ICA-DM连接性与年龄呈负相关。在所有DM区域，ICA体素权重与年龄存在不同程度的负相关。作为一种替代方法，我们生成了一个分布式DM空间模板，并评估了每个个体DM成分与该模板拟合度与年龄的相关性。使用“留一法”程序，我们讨论了从DM模板生成过程中消除偏差的重要性。
