Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon 305-701, Korea.
Korean J Radiol. 2012 May-Jun;13(3):265-74. doi: 10.3348/kjr.2012.13.3.265. Epub 2012 Apr 17.
Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs).
This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers.
We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation).
RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.
静息态网络(RSNs),包括默认模式网络(DMN),已被认为是大脑状态的标志物,如意识、发育变化和治疗效果。RSNs 之间功能连接的一致性尚未得到充分探索,尤其是在与静息态相关的独立成分(RSICs)之间。
这项静息态 fMRI 研究旨在探讨 13 名健康志愿者在“第 1 天”和“4 周后”之间,RSICs 之间的功能连接一致性以及它们之间的空间一致性。
我们发现,大多数 RSICs,尤其是 DMN,在时间上具有可重复性,而一些 RSICs 在其空间特征或功能连接方面存在可变性。在基底神经节、左额顶网络的顶叶区域和辅助运动区发现相对较低的空间一致性。无论使用哪种相关分析方法(Pearson 或偏相关),两个独立成分(双侧角回/缘上回/顶内回和双侧颞叶/枕叶回)之间的功能连接在整个时间过程中都呈下降趋势。
在空间特征和功能连接方面,表现出可变一致性的 RSICs 是不同的。为了理解大脑作为一个动态网络,我们建议进一步研究特定区域的激活变化和大脑网络中功能连接的调节。