Functional Segmentation of the Brain Cortex Using High Model Order Group PICA
Functional Segmentation of the Brain Cortex Using High Model Order Group PICA
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DOI：
10.1002/hbm.20813
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发表时间：
2009-12-01
影响因子：
4.8
通讯作者：
Tervonen, Osmo
中科院分区：
文献类型：
--
作者：
Kiviniemi, Vesa;Starck, Tuomo;Tervonen, Osmo
静息状态脑网络（RSN）的基线活动已成为神经影像学中发展最快的研究课题之一。它已被证明，高达12 RSN可以区分使用独立成分分析（伊卡）的血氧水平依赖（BOLD）的静息状态数据。在这项研究中，我们研究了有多少16 N信号源可以从整个大脑皮层分离使用高维伊卡分析从一组数据集。使用时间连接和概率独立成分分析算法对55名受试者的组数据进行了分析。伊卡重复性测试验证了70个计算分量中的60个是鲁棒可检测的。42个独立信号源可识别为RSN，28个与伪影或其他非感兴趣源（非RSN）相关。所描述的RSN比之前报告的RSN组件更接近功能性神经解剖结构。非RSN源的时间源间连接性显著低于RSN源（P < 0.0003）。我们的结论是，高模型阶伊卡的组BOLD数据，使大脑皮层的功能分割。该方法使新的方法，因果关系和连接分析与更具体的解剖细节。《脑图谱》30：3865-3886，2009年。(C)2009 Wiley-Liss，Inc.
Baseline activity of resting state brain networks (RSN) in a resting subject has become one of the fastest growing research topics in neuroimaging. It has been shown that up to 12 RSNs can be differentiated using an independent component analysis (ICA) of the blood oxygen level dependent (BOLD) resting state data. In this study, we investigate how many 16N signal sources can be separated from the entire brain cortex using high dimension ICA analysis from a group dataset. Group data from 55 subjects was analyzed using temporal concatenation and a probabilistic independent component analysis algorithm. ICA repeatability testing verified that 60 of the 70 computed components were robustly detectable. Forty-two independent signal sources were identifiable as RSN, and 28 were related to artifacts or other noninterest sources (non-RSN). The depicted RSNs bore a closer match to functional neuroanatomy than the previously reported RSN components. The non-RSN sources have significantly lower temporal intersource connectivity than the RSN (P < 0.0003). We conclude that the high model order ICA of the group BOLD data enables functional segmentation of the brain cortex. The method enables new approaches to causality and connectivity analysis with more specific anatomical details. Hum Brain Mapp 30:3865-3886, 2009. (C) 2009 Wiley-Liss, Inc.